const automl = require('@google-cloud/automl');
  const fs = require('fs');

  // Create client for prediction service.
  const client = new automl.PredictionServiceClient();

  /**
   * TODO(developer): Uncomment the following line before running the sample.
   */
  // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
  // const computeRegion = `region-name, e.g. "us-central1"`;
  // const modelId = `id of the model, e.g. “ICN723541179344731436”`;
  // const filePath = `local text file path of content to be classified, e.g. "./resources/flower.png"`;
  // const scoreThreshold = `value between 0.0 and 1.0, e.g. "0.5"`;

  // Get the full path of the model.
  const modelFullId = client.modelPath(projectId, computeRegion, modelId);

  // Read the file content for prediction.
  const content = fs.readFileSync(filePath, 'base64');

  const params = {};

  if (scoreThreshold) {
    params.score_threshold = scoreThreshold;
  }

  // Set the payload by giving the content and type of the file.
  const payload = {};
  payload.image = {imageBytes: content};

  // params is additional domain-specific parameters.
  // currently there is no additional parameters supported.
  const [response] = await client.predict({
    name: modelFullId,
    payload: payload,
    params: params,
  });
  console.log(`Prediction results:`);
  response.payload.forEach(result => {
    console.log(`Predicted class name: ${result.displayName}`);
    console.log(`Predicted class score: ${result.classification.score}`);
  });