import { OrqCore } from "../core.js";
import { RequestOptions } from "../lib/sdks.js";
import { ConnectionError, InvalidRequestError, RequestAbortedError, RequestTimeoutError, UnexpectedClientError } from "../models/errors/httpclienterrors.js";
import { OrqError } from "../models/errors/orqerror.js";
import { ResponseValidationError } from "../models/errors/responsevalidationerror.js";
import { SDKValidationError } from "../models/errors/sdkvalidationerror.js";
import * as operations from "../models/operations/index.js";
import { APIPromise } from "../types/async.js";
import { Result } from "../types/fp.js";
/**
 * Create embeddings
 *
 * @remarks
 * Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.
 */
export declare function routerEmbeddingsCreate(client: OrqCore, request: operations.CreateEmbeddingRequestBody, options?: RequestOptions): APIPromise<Result<operations.CreateEmbeddingResponseBody, OrqError | ResponseValidationError | ConnectionError | RequestAbortedError | RequestTimeoutError | InvalidRequestError | UnexpectedClientError | SDKValidationError>>;
//# sourceMappingURL=routerEmbeddingsCreate.d.ts.map