/*! @azure/msal-node v3.8.1 2025-10-29 */
'use strict';
import { BaseManagedIdentitySource, ManagedIdentityUserAssignedIdQueryParameterNames } from './BaseManagedIdentitySource.mjs';
import { ManagedIdentityEnvironmentVariableNames, ManagedIdentitySourceNames, ManagedIdentityHeaders, ManagedIdentityQueryParameters, ManagedIdentityIdType, HttpMethod } from '../../utils/Constants.mjs';
import { ManagedIdentityRequestParameters } from '../../config/ManagedIdentityRequestParameters.mjs';

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

export { MANAGED_IDENTITY_MACHINE_LEARNING_UNSUPPORTED_ID_TYPE_ERROR, MachineLearning };
//# sourceMappingURL=MachineLearning.mjs.map
