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   * Licensed to the Apache Software Foundation (ASF) under one
   * or more contributor license agreements.  See the NOTICE file
   * distributed with this work for additional information
   * regarding copyright ownership.  The ASF licenses this file
   * to you 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,
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   * See the License for the specific language governing permissions and
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  package org.apache.beam.sdk.extensions.ml;
  
  import static org.junit.Assert.assertTrue;
  
  import com.google.api.client.json.GenericJson;
  import com.google.cloud.recommendationengine.v1beta1.PredictResponse;
  import java.util.ArrayList;
  import java.util.Arrays;
  import java.util.List;
  import org.apache.beam.sdk.extensions.gcp.options.GcpOptions;
  import org.apache.beam.sdk.testing.PAssert;
  import org.apache.beam.sdk.testing.TestPipeline;
  import org.apache.beam.sdk.transforms.Create;
  import org.apache.beam.sdk.transforms.SerializableFunction;
  import org.apache.beam.sdk.values.PCollectionTuple;
  import org.junit.Ignore;
  import org.junit.Rule;
  import org.junit.Test;
  import org.junit.runner.RunWith;
  import org.junit.runners.JUnit4;
  
  @RunWith(JUnit4.class)
  public class RecommendationAIPredictIT {
    @Rule public TestPipeline testPipeline = TestPipeline.create();
  
    public static GenericJson getUserEvent() {
      GenericJson userInfo = new GenericJson().set("visitorId", "1");
      return new GenericJson().set("eventType", "home-page-view").set("userInfo", userInfo);
    }
  
    @Ignore("https://issues.apache.org/jira/browse/BEAM-12733")
    @Test
    public void predict() {
      String projectId = testPipeline.getOptions().as(GcpOptions.class).getProject();
  
      PCollectionTuple predictResult =
          testPipeline
              .apply(
                  Create.of(Arrays.asList(getUserEvent()))
                      .withCoder(GenericJsonCoder.of(GenericJson.class)))
              .apply(
                  RecommendationAIIO.predictAll()
                      .withProjectId(projectId)
                      .withPlacementId("recently_viewed_default"));
      PAssert.that(predictResult.get(RecommendationAIPredict.SUCCESS_TAG))
          .satisfies(new VerifyPredictResult());
      testPipeline.run().waitUntilFinish();
    }
  
    private static class VerifyPredictResult
        implements SerializableFunction<Iterable<PredictResponse.PredictionResult>, Void> {
  
      @Override
      public Void apply(Iterable<PredictResponse.PredictionResult> input) {
        List<PredictResponse.PredictionResult> matches = new ArrayList<>();
        input.forEach(
            item -> {
              PredictResponse.PredictionResult result = item;
              matches.add(result);
            });
        assertTrue(!matches.isEmpty());
        return null;
      }
    }
  }
  