/*
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* Copyright (c) Microsoft Corporation. All rights reserved.
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* Licensed under the MIT License.
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*/
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import { INetworkModule, Logger } from "@azure/msal-common/node";
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import {
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BaseManagedIdentitySource,
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ManagedIdentityUserAssignedIdQueryParameterNames,
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} from "./BaseManagedIdentitySource.js";
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import {
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HttpMethod,
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ManagedIdentityEnvironmentVariableNames,
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ManagedIdentitySourceNames,
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ManagedIdentityIdType,
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ManagedIdentityQueryParameters,
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ManagedIdentityHeaders,
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} from "../../utils/Constants.js";
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import { CryptoProvider } from "../../crypto/CryptoProvider.js";
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import { ManagedIdentityRequestParameters } from "../../config/ManagedIdentityRequestParameters.js";
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import { ManagedIdentityId } from "../../config/ManagedIdentityId.js";
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import { NodeStorage } from "../../cache/NodeStorage.js";
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const MACHINE_LEARNING_MSI_API_VERSION: string = "2017-09-01";
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export const MANAGED_IDENTITY_MACHINE_LEARNING_UNSUPPORTED_ID_TYPE_ERROR = `Only client id is supported for user-assigned managed identity in ${ManagedIdentitySourceNames.MACHINE_LEARNING}.`; // referenced in unit test
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/**
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* Machine Learning Managed Identity Source implementation for Azure Machine Learning environments.
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*
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* This class handles managed identity authentication specifically for Azure Machine Learning services.
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* It supports both system-assigned and user-assigned managed identities, using the MSI_ENDPOINT
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* and MSI_SECRET environment variables that are automatically provided in Azure ML environments.
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*/
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export class MachineLearning extends BaseManagedIdentitySource {
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private msiEndpoint: string;
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private secret: string;
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/**
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* Creates a new MachineLearning managed identity source instance.
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*
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* @param logger - Logger instance for diagnostic information
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* @param nodeStorage - Node storage implementation for caching
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* @param networkClient - Network client for making HTTP requests
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* @param cryptoProvider - Cryptographic operations provider
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* @param disableInternalRetries - Whether to disable automatic request retries
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* @param msiEndpoint - The MSI endpoint URL from environment variables
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* @param secret - The MSI secret from environment variables
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*/
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constructor(
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logger: Logger,
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nodeStorage: NodeStorage,
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networkClient: INetworkModule,
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cryptoProvider: CryptoProvider,
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disableInternalRetries: boolean,
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msiEndpoint: string,
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secret: string
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) {
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super(
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logger,
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nodeStorage,
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networkClient,
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cryptoProvider,
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disableInternalRetries
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);
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this.msiEndpoint = msiEndpoint;
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this.secret = secret;
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}
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/**
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* Retrieves the required environment variables for Azure Machine Learning managed identity.
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*
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* This method checks for the presence of MSI_ENDPOINT and MSI_SECRET environment variables
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* that are automatically set by the Azure Machine Learning platform when managed identity
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* is enabled for the compute instance or cluster.
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*
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* @returns An array containing [msiEndpoint, secret] where either value may be undefined
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* if the corresponding environment variable is not set
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*/
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public static getEnvironmentVariables(): Array<string | undefined> {
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const msiEndpoint: string | undefined =
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process.env[ManagedIdentityEnvironmentVariableNames.MSI_ENDPOINT];
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const secret: string | undefined =
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process.env[ManagedIdentityEnvironmentVariableNames.MSI_SECRET];
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return [msiEndpoint, secret];
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}
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/**
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* Attempts to create a MachineLearning managed identity source.
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*
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* This method validates the Azure Machine Learning environment by checking for the required
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* MSI_ENDPOINT and MSI_SECRET environment variables. If both are present and valid,
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* it creates and returns a MachineLearning instance. If either is missing or invalid,
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* it returns null, indicating that this managed identity source is not available
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* in the current environment.
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*
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* @param logger - Logger instance for diagnostic information
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* @param nodeStorage - Node storage implementation for caching
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* @param networkClient - Network client for making HTTP requests
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* @param cryptoProvider - Cryptographic operations provider
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* @param disableInternalRetries - Whether to disable automatic request retries
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*
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* @returns A new MachineLearning instance if the environment is valid, null otherwise
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*/
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public static tryCreate(
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logger: Logger,
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nodeStorage: NodeStorage,
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networkClient: INetworkModule,
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cryptoProvider: CryptoProvider,
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disableInternalRetries: boolean
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): MachineLearning | null {
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const [msiEndpoint, secret] = MachineLearning.getEnvironmentVariables();
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// if either of the MSI endpoint or MSI secret variables are undefined, this MSI provider is unavailable.
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if (!msiEndpoint || !secret) {
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logger.info(
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`[Managed Identity] ${ManagedIdentitySourceNames.MACHINE_LEARNING} managed identity is unavailable because one or both of the '${ManagedIdentityEnvironmentVariableNames.MSI_ENDPOINT}' and '${ManagedIdentityEnvironmentVariableNames.MSI_SECRET}' environment variables are not defined.`,
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""
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);
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return null;
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}
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const validatedMsiEndpoint: string =
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MachineLearning.getValidatedEnvVariableUrlString(
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ManagedIdentityEnvironmentVariableNames.MSI_ENDPOINT,
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msiEndpoint,
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ManagedIdentitySourceNames.MACHINE_LEARNING,
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logger
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);
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logger.info(
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`[Managed Identity] Environment variables validation passed for ${ManagedIdentitySourceNames.MACHINE_LEARNING} managed identity. Endpoint URI: ${validatedMsiEndpoint}. Creating ${ManagedIdentitySourceNames.MACHINE_LEARNING} managed identity.`,
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""
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);
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return new MachineLearning(
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logger,
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nodeStorage,
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networkClient,
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cryptoProvider,
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disableInternalRetries,
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msiEndpoint,
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secret
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);
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}
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/**
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* Creates a managed identity token request for Azure Machine Learning environments.
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*
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* This method constructs the HTTP request parameters needed to acquire an access token
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* from the Azure Machine Learning managed identity endpoint. It handles both system-assigned
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* and user-assigned managed identities with specific logic for each type:
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*
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* - System-assigned: Uses the DEFAULT_IDENTITY_CLIENT_ID environment variable
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* - User-assigned: Only supports client ID-based identification (not object ID or resource ID)
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*
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* The request uses the 2017-09-01 API version and includes the required secret header
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* for authentication with the MSI endpoint.
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*
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* @param resource - The target resource/scope for which to request an access token (e.g., "https://graph.microsoft.com/.default")
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* @param managedIdentityId - The managed identity configuration specifying whether to use system-assigned or user-assigned identity
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*
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* @returns A configured ManagedIdentityRequestParameters object ready for network execution
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*
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* @throws Error if an unsupported managed identity ID type is specified (only client ID is supported for user-assigned)
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*/
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public createRequest(
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resource: string,
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managedIdentityId: ManagedIdentityId
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): ManagedIdentityRequestParameters {
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const request: ManagedIdentityRequestParameters =
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new ManagedIdentityRequestParameters(
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HttpMethod.GET,
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this.msiEndpoint
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);
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request.headers[ManagedIdentityHeaders.METADATA_HEADER_NAME] = "true";
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request.headers[ManagedIdentityHeaders.ML_AND_SF_SECRET_HEADER_NAME] =
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this.secret;
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request.queryParameters[ManagedIdentityQueryParameters.API_VERSION] =
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MACHINE_LEARNING_MSI_API_VERSION;
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request.queryParameters[ManagedIdentityQueryParameters.RESOURCE] =
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resource;
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if (
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managedIdentityId.idType === ManagedIdentityIdType.SYSTEM_ASSIGNED
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) {
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request.queryParameters[
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ManagedIdentityUserAssignedIdQueryParameterNames.MANAGED_IDENTITY_CLIENT_ID_2017
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] = process.env[
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ManagedIdentityEnvironmentVariableNames
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.DEFAULT_IDENTITY_CLIENT_ID
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] as string; // this environment variable is always set in an Azure Machine Learning source
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} else if (
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managedIdentityId.idType ===
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ManagedIdentityIdType.USER_ASSIGNED_CLIENT_ID
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) {
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request.queryParameters[
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this.getManagedIdentityUserAssignedIdQueryParameterKey(
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managedIdentityId.idType,
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false, // isIMDS
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true // uses2017API
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)
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] = managedIdentityId.id;
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} else {
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throw new Error(
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MANAGED_IDENTITY_MACHINE_LEARNING_UNSUPPORTED_ID_TYPE_ERROR
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);
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}
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// bodyParameters calculated in BaseManagedIdentity.acquireTokenWithManagedIdentity
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return request;
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}
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}
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