How to use the @google-cloud/automl.PredictionServiceClient function in @google-cloud/automl

// limitations under the License.

// Replace the strings below with your own project & model info
const project = 'YOUR_PROJECT_NAME';
const region = 'YOUR_PROJECT_REGION';
const automl_model = 'YOUR_AUTOML_MODEL_ID';

const sizeOf = require('image-size');
const fs = require('fs');
const exec = require('child_process').exec;

// GCP libraries
const gcs = require('@google-cloud/storage');
const gcsClient = new gcs();
const automl = require('@google-cloud/automl');
const predictionClient = new automl.PredictionServiceClient();

// Firebase libraries
const functions = require('firebase-functions');
const admin = require('firebase-admin');
const db = admin.firestore();
admin.initializeApp(functions.config().firebase);

function resizeImg(filepath) {
    return new Promise((resolve, reject) => {
        exec(`convert ${filepath} -resize 600x ${filepath}`, (err) => {
          if (err) {
            console.error('Failed to resize image', err);
            reject(err);
          } else {
            console.log('resized image successfully');
            resolve(filepath);

async function main(
  projectId,
  computeRegion,
  modelId,
  filePath,
  scoreThreshold
) {
  // [START automl_quickstart]
  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');

* Demonstrates using the AutoML client to detect the object in an image.
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // const projectId = '[PROJECT_ID]' e.g., "my-gcloud-project";
  // const computeRegion = '[REGION_NAME]' e.g., "us-central1";
  // const modelId = '[MODEL_ID]' e.g., "IOD1187015161160925184";
  // const filePath = '[GCS_PATH]' e.g., "/home/ubuntu/salad.jpg",
  // `local text file path of content to be extracted`;
  // const scoreThreshold = '[SCORE_THRESHOLD]', e.g, 0.50 ,
  // `Set the score threshold for Prediction of the created model`;

  //Imports the Google Cloud Automl library
  const {PredictionServiceClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const predictionServiceClient = new PredictionServiceClient();

  const fs = require(`fs`);

  async function predict() {
    // Get the full path of the model.
    const modelFullId = predictionServiceClient.modelPath(
      projectId,
      computeRegion,
      modelId
    );

    // Read the file content for prediction.
    const content = fs.readFileSync(filePath, `base64`);
    let params = {};
    if (scoreThreshold) {
      params = {