Examples with PredictResponse com.google.cloud.aiplatform.v1.PredictResponse used on opensource projects

Example 11 with PredictResponse

use of com.google.cloud.aiplatform.v1.PredictResponse in project java-automl by googleapis.

the class TranslatePredict method predict.

static void predict(String projectId, String modelId, String filePath) throws IOException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient client = PredictionServiceClient.create()) {
        // Get the full path of the model.
        ModelName name = ModelName.of(projectId, "us-central1", modelId);
        String content = new String(Files.readAllBytes(Paths.get(filePath)));
        TextSnippet textSnippet = TextSnippet.newBuilder().setContent(content).build();
        ExamplePayload payload = ExamplePayload.newBuilder().setTextSnippet(textSnippet).build();
        PredictRequest predictRequest = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).build();
        PredictResponse response = client.predict(predictRequest);
        TextSnippet translatedContent = response.getPayload(0).getTranslation().getTranslatedContent();
        System.out.format("Translated Content: %s\n", translatedContent.getContent());
    }
}

Example 12 with PredictResponse

use of com.google.cloud.aiplatform.v1.PredictResponse in project java-automl by googleapis.

the class TablesPredict method predict.

static void predict(String projectId, String modelId, List<Value> values) throws IOException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient client = PredictionServiceClient.create()) {
        // Get the full path of the model.
        ModelName name = ModelName.of(projectId, "us-central1", modelId);
        Row row = Row.newBuilder().addAllValues(values).build();
        ExamplePayload payload = ExamplePayload.newBuilder().setRow(row).build();
        // Feature importance gives you visibility into how the features in a specific prediction
        // request informed the resulting prediction. For more info, see:
        // https://cloud.google.com/automl-tables/docs/features#local
        PredictRequest request = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).putParams("feature_importance", "true").build();
        PredictResponse response = client.predict(request);
        System.out.println("Prediction results:");
        for (AnnotationPayload annotationPayload : response.getPayloadList()) {
            TablesAnnotation tablesAnnotation = annotationPayload.getTables();
            System.out.format("Classification label: %s%n", tablesAnnotation.getValue().getStringValue());
            System.out.format("Classification score: %.3f%n", tablesAnnotation.getScore());
            // Get features of top importance
            tablesAnnotation.getTablesModelColumnInfoList().forEach(info -> System.out.format("\tColumn: %s - Importance: %.2f%n", info.getColumnDisplayName(), info.getFeatureImportance()));
        }
    }
}

Example 13 with PredictResponse

use of com.google.cloud.aiplatform.v1.PredictResponse in project java-automl by googleapis.

the class LanguageTextClassificationPredict method predict.

static void predict(String projectId, String modelId, String content) throws IOException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient client = PredictionServiceClient.create()) {
        // Get the full path of the model.
        ModelName name = ModelName.of(projectId, "us-central1", modelId);
        // For available mime types, see:
        // https://cloud.google.com/automl/docs/reference/rest/v1/projects.locations.models/predict#textsnippet
        TextSnippet textSnippet = TextSnippet.newBuilder().setContent(content).setMimeType(// Types: text/plain, text/html
        "text/plain").build();
        ExamplePayload payload = ExamplePayload.newBuilder().setTextSnippet(textSnippet).build();
        PredictRequest predictRequest = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).build();
        PredictResponse response = client.predict(predictRequest);
        for (AnnotationPayload annotationPayload : response.getPayloadList()) {
            System.out.format("Predicted class name: %s\n", annotationPayload.getDisplayName());
            System.out.format("Predicted sentiment score: %.2f\n\n", annotationPayload.getClassification().getScore());
        }
    }
}

Example 14 with PredictResponse

use of com.google.cloud.aiplatform.v1.PredictResponse in project java-aiplatform by googleapis.

the class PredictTabularRegressionSample method predictTabularRegression.

static void predictTabularRegression(String instance, String project, String endpointId) throws IOException {
    PredictionServiceSettings predictionServiceSettings = PredictionServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create(predictionServiceSettings)) {
        String location = "us-central1";
        EndpointName endpointName = EndpointName.of(project, location, endpointId);
        ListValue.Builder listValue = ListValue.newBuilder();
        JsonFormat.parser().merge(instance, listValue);
        List<Value> instanceList = listValue.getValuesList();
        Value parameters = Value.newBuilder().setListValue(listValue).build();
        PredictResponse predictResponse = predictionServiceClient.predict(endpointName, instanceList, parameters);
        System.out.println("Predict Tabular Regression Response");
        System.out.format("\tDisplay Model Id: %s\n", predictResponse.getDeployedModelId());
        System.out.println("Predictions");
        for (Value prediction : predictResponse.getPredictionsList()) {
            TabularRegressionPredictionResult.Builder resultBuilder = TabularRegressionPredictionResult.newBuilder();
            TabularRegressionPredictionResult result = (TabularRegressionPredictionResult) ValueConverter.fromValue(resultBuilder, prediction);
            System.out.printf("\tUpper bound: %f\n", result.getUpperBound());
            System.out.printf("\tLower bound: %f\n", result.getLowerBound());
            System.out.printf("\tValue: %f\n", result.getValue());
        }
    }
}

Example 15 with PredictResponse

use of com.google.cloud.aiplatform.v1.PredictResponse in project java-aiplatform by googleapis.

the class PredictTextClassificationSingleLabelSample method predictTextClassificationSingleLabel.

static void predictTextClassificationSingleLabel(String project, String content, String endpointId) throws IOException {
    PredictionServiceSettings predictionServiceSettings = PredictionServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create(predictionServiceSettings)) {
        String location = "us-central1";
        EndpointName endpointName = EndpointName.of(project, location, endpointId);
        TextClassificationPredictionInstance predictionInstance = TextClassificationPredictionInstance.newBuilder().setContent(content).build();
        List<Value> instances = new ArrayList<>();
        instances.add(ValueConverter.toValue(predictionInstance));
        PredictResponse predictResponse = predictionServiceClient.predict(endpointName, instances, ValueConverter.EMPTY_VALUE);
        System.out.println("Predict Text Classification Response");
        System.out.format("\tDeployed Model Id: %s\n", predictResponse.getDeployedModelId());
        System.out.println("Predictions:\n\n");
        for (Value prediction : predictResponse.getPredictionsList()) {
            ClassificationPredictionResult.Builder resultBuilder = ClassificationPredictionResult.newBuilder();
            // Display names and confidences values correspond to
            // IDs in the ID list.
            ClassificationPredictionResult result = (ClassificationPredictionResult) ValueConverter.fromValue(resultBuilder, prediction);
            int counter = 0;
            for (Long id : result.getIdsList()) {
                System.out.printf("Label ID: %d\n", id);
                System.out.printf("Label: %s\n", result.getDisplayNames(counter));
                System.out.printf("Confidence: %.4f\n", result.getConfidences(counter));
                counter++;
            }
        }
    }
}