Examples with MLPredictionTaskRequest org.opensearch.ml.common.transport.prediction.MLPredictionTaskRequest used on opensource projects

Example 6 with MLPredictionTaskRequest

use of org.opensearch.ml.common.transport.prediction.MLPredictionTaskRequest in project ml-commons by opensearch-project.

the class RestMLPredictionAction method getRequest.

/**
 * Creates a MLPredictionTaskRequest from a RestRequest
 *
 * @param request RestRequest
 * @return MLPredictionTaskRequest
 */
@VisibleForTesting
MLPredictionTaskRequest getRequest(RestRequest request) throws IOException {
    String algorithm = getAlgorithm(request);
    String modelId = getParameterId(request, PARAMETER_MODEL_ID);
    XContentParser parser = request.contentParser();
    ensureExpectedToken(XContentParser.Token.START_OBJECT, parser.nextToken(), parser);
    MLInput mlInput = MLInput.parse(parser, algorithm);
    return new MLPredictionTaskRequest(modelId, mlInput);
}

Example 7 with MLPredictionTaskRequest

use of org.opensearch.ml.common.transport.prediction.MLPredictionTaskRequest in project ml-commons by opensearch-project.

the class TransportPredictionTaskAction method doExecute.

@Override
protected void doExecute(Task task, ActionRequest request, ActionListener<MLTaskResponse> listener) {
    MLPredictionTaskRequest mlPredictionTaskRequest = MLPredictionTaskRequest.fromActionRequest(request);
    mlPredictTaskRunner.run(mlPredictionTaskRequest, transportService, listener);
}

Example 8 with MLPredictionTaskRequest

use of org.opensearch.ml.common.transport.prediction.MLPredictionTaskRequest in project ml-commons by opensearch-project.

the class IntegTestUtils method predictAndVerifyResult.

// Predict with the model generated, and verify the prediction result.
public static void predictAndVerifyResult(String taskId, MLInputDataset inputDataset) throws IOException {
    MLInput mlInput = MLInput.builder().algorithm(FunctionName.KMEANS).inputDataset(inputDataset).build();
    MLPredictionTaskRequest predictionRequest = new MLPredictionTaskRequest(taskId, mlInput);
    ActionFuture<MLTaskResponse> predictionFuture = client().execute(MLPredictionTaskAction.INSTANCE, predictionRequest);
    MLTaskResponse predictionResponse = predictionFuture.actionGet();
    XContentBuilder builder = XContentFactory.contentBuilder(XContentType.JSON);
    builder.startObject();
    MLPredictionOutput mlPredictionOutput = (MLPredictionOutput) predictionResponse.getOutput();
    mlPredictionOutput.getPredictionResult().toXContent(builder, ToXContent.EMPTY_PARAMS);
    builder.endObject();
    String jsonStr = Strings.toString(builder);
    String expectedStr1 = "{\"column_metas\":[{\"name\":\"ClusterID\",\"column_type\":\"INTEGER\"}]," + "\"rows\":[{\"values\":[{\"column_type\":\"INTEGER\",\"value\":0}]}]}";
    String expectedStr2 = "{\"column_metas\":[{\"name\":\"ClusterID\",\"column_type\":\"INTEGER\"}]," + "\"rows\":[{\"values\":[{\"column_type\":\"INTEGER\",\"value\":1}]}]}";
    // The prediction result would not be a fixed value.
    assertTrue(expectedStr1.equals(jsonStr) || expectedStr2.equals(jsonStr));
}