import { Command as $Command } from "@smithy/smithy-client"; import { MetadataBearer as __MetadataBearer } from "@smithy/types"; import { CreateProjectInput, CreateProjectOutput } from "../models/models_2"; import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient"; /** * @public */ export type { __MetadataBearer }; export { $Command }; /** * @public * * The input for {@link CreateProjectCommand}. */ export interface CreateProjectCommandInput extends CreateProjectInput { } /** * @public * * The output of {@link CreateProjectCommand}. */ export interface CreateProjectCommandOutput extends CreateProjectOutput, __MetadataBearer { } declare const CreateProjectCommand_base: { new (input: CreateProjectCommandInput): import("@smithy/smithy-client").CommandImpl; new (input: CreateProjectCommandInput): import("@smithy/smithy-client").CommandImpl; getEndpointParameterInstructions(): import("@smithy/middleware-endpoint").EndpointParameterInstructions; }; /** *

Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.

* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript * import { SageMakerClient, CreateProjectCommand } from "@aws-sdk/client-sagemaker"; // ES Modules import * // const { SageMakerClient, CreateProjectCommand } = require("@aws-sdk/client-sagemaker"); // CommonJS import * const client = new SageMakerClient(config); * const input = { // CreateProjectInput * ProjectName: "STRING_VALUE", // required * ProjectDescription: "STRING_VALUE", * ServiceCatalogProvisioningDetails: { // ServiceCatalogProvisioningDetails * ProductId: "STRING_VALUE", // required * ProvisioningArtifactId: "STRING_VALUE", * PathId: "STRING_VALUE", * ProvisioningParameters: [ // ProvisioningParameters * { // ProvisioningParameter * Key: "STRING_VALUE", * Value: "STRING_VALUE", * }, * ], * }, * Tags: [ // TagList * { // Tag * Key: "STRING_VALUE", // required * Value: "STRING_VALUE", // required * }, * ], * TemplateProviders: [ // CreateTemplateProviderList * { // CreateTemplateProvider * CfnTemplateProvider: { // CfnCreateTemplateProvider * TemplateName: "STRING_VALUE", // required * TemplateURL: "STRING_VALUE", // required * RoleARN: "STRING_VALUE", * Parameters: [ // CfnStackCreateParameters * { // CfnStackCreateParameter * Key: "STRING_VALUE", // required * Value: "STRING_VALUE", * }, * ], * }, * }, * ], * }; * const command = new CreateProjectCommand(input); * const response = await client.send(command); * // { // CreateProjectOutput * // ProjectArn: "STRING_VALUE", // required * // ProjectId: "STRING_VALUE", // required * // }; * * ``` * * @param CreateProjectCommandInput - {@link CreateProjectCommandInput} * @returns {@link CreateProjectCommandOutput} * @see {@link CreateProjectCommandInput} for command's `input` shape. * @see {@link CreateProjectCommandOutput} for command's `response` shape. * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) *

You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.

* * @throws {@link SageMakerServiceException} *

Base exception class for all service exceptions from SageMaker service.

* * * @public */ export declare class CreateProjectCommand extends CreateProjectCommand_base { /** @internal type navigation helper, not in runtime. */ protected static __types: { api: { input: CreateProjectInput; output: CreateProjectOutput; }; sdk: { input: CreateProjectCommandInput; output: CreateProjectCommandOutput; }; }; }