old_contents: /**
   * Copyright 2018, Google, Inc.
   * Licensed under the Apache License, Version 2.0 (the "License");
   * you may not use this file except in compliance with the License.
   * You may obtain a copy of the License at
   *
   *    http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  
  'use strict';
  
  // [START automl_quickstart]
  // TBD
  // [END automl_quickstart]
  
  
new_contents: /**
   * Copyright 2019, Google, Inc.
   * Licensed under the Apache License, Version 2.0 (the "License");
   * you may not use this file except in compliance with the License.
   * You may obtain a copy of the License at
   *
   *    http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  
  'use strict';
  
  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');
  
    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}`);
    });
    // [END automl_quickstart]
  }
  main(...process.argv.slice(2)).catch(err => {
    console.error(err);
    process.exitCode = 1;
  });
  
subject: add .repo-metadata.json; allows us to generate new docs site (#183)