@axflow/models/dist/openai/embedding.d.mts

Zero-dependency, modular SDK for building robust natural language applications

type SharedRequestOptions = {
    apiKey?: string;
    apiUrl?: string;
    fetch?: typeof fetch;
    headers?: Record<string, string>;
    signal?: AbortSignal;
};

declare namespace OpenAIEmbeddingTypes {
    type RequestOptions = SharedRequestOptions;
    type Request = {
        input: string | Array<string> | Array<number> | Array<Array<number>>;
        model: string;
        user?: string;
    };
    type EmbeddingObject = {
        index: number;
        object: 'embedding';
        embedding: number[];
    };
    type Response = {
        object: 'list';
        data: EmbeddingObject[];
        model: string;
        usage: {
            prompt_tokens: number;
            total_tokens: number;
        };
    };
}
/**
 * Calculate text embeddings using the OpenAI API.
 *
 * @see https://platform.openai.com/docs/api-reference/embeddings
 *
 * @param request The request body sent to OpenAI. See OpenAI's documentation for /v1/embeddings for supported parameters.
 * @param options
 * @param options.apiKey OpenAI API key.
 * @param options.apiUrl The url of the OpenAI (or compatible) API. Defaults to https://api.openai.com/v1/embeddings.
 * @param options.fetch A custom implementation of fetch. Defaults to globalThis.fetch.
 * @param options.headers Optionally add additional HTTP headers to the request.
 * @param options.signal An AbortSignal that can be used to abort the fetch request.
 * @returns An object consisting of the text embeddings and other metadata. See OpenAI's documentation for /v1/embeddings.
 */
declare function run(request: OpenAIEmbeddingTypes.Request, options: OpenAIEmbeddingTypes.RequestOptions): Promise<OpenAIEmbeddingTypes.Response>;
declare class OpenAIEmbedding {
    static run: typeof run;
}

export { OpenAIEmbedding, OpenAIEmbeddingTypes };