import * as AWS from 'aws-sdk';
    import SageMaker from 'aws-sdk/clients/sagemaker';

    // Reusable function to add the XSRF token header to a request
    function addXsrfToken<D, E>(request: AWS.Request<D, E>) {
      const cookie = document.cookie.match('\\b' + '_xsrf' + '=([^;]*)\\b');
      const xsrfToken = cookie ? cookie[1] : undefined;
      if (xsrfToken !== undefined) {
        request.httpRequest.headers['X-XSRFToken'] = xsrfToken;
      }
    }

    // These credentials are *not* used for the actual AWS service call but you have
    // to provide any dummy credentials (Not real ones!)
    AWS.config.secretAccessKey = 'IGNOREDIGNORE/IGNOREDIGNOREDIGNOREDIGNOR';
    AWS.config.accessKeyId = 'IGNOREDIGNO';

    // Change the endpoint in the client to the "awsproxy" endpoint on the Jupyter server.
    const proxyEndpoint = 'http://localhost:8888/awsproxy';

    const sageMakerClient = new SageMaker({
        region: 'us-west-2',
        endpoint: proxyEndpoint,
    });

    // Make the API call!
    await sageMakerClient
        .listNotebookInstances({
            NameContains: 'jaipreet'
        })
        .on('build', addXsrfToken)
        .promise();

    import S3 from 'aws-sdk/clients/s3';

    const s3Client = new S3({
        region: 'us-west-2',
        endpoint: proxyEndpoint,
        s3ForcePathStyle: true,
        s3DisableBodySigning:false // for https
    });

    await s3Client
        .getObject({
            Bucket: 'my-bucket',
            Key: 'my-object'
        })
        .on('build', addXsrfToken)
        .promise();