Fixed error for case when mltensor has data as null

Signed-off-by: Martin Gaievski <[email protected]>
opensearch-project · Oct 6, 2023 · e592ad7 · e592ad7
1 parent 841f280
commit e592ad7
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diff --git a/src/main/java/org/opensearch/neuralsearch/ml/MLCommonsClientAccessor.java b/src/main/java/org/opensearch/neuralsearch/ml/MLCommonsClientAccessor.java
@@ -12,12 +12,14 @@
 import java.util.Arrays;
 import java.util.List;
 import java.util.Map;
+import java.util.Objects;
 import java.util.stream.Collectors;
 
 import lombok.NonNull;
 import lombok.RequiredArgsConstructor;
 import lombok.extern.log4j.Log4j2;
 
+import org.apache.logging.log4j.util.Strings;
 import org.opensearch.core.action.ActionListener;
 import org.opensearch.core.common.util.CollectionUtils;
 import org.opensearch.ml.client.MachineLearningNodeClient;
@@ -40,6 +42,7 @@
 public class MLCommonsClientAccessor {
     private static final List<String> TARGET_RESPONSE_FILTERS = List.of("sentence_embedding");
     private final MachineLearningNodeClient mlClient;
+    private static final String EXCEPTION_MESSAGE_MODEL_PROCESSING_FAILED = "the system encountered an unexpected error during processing";
 
     /**
      * Wrapper around {@link #inferenceSentences} that expected a single input text and produces a single floating
@@ -187,6 +190,13 @@ private List<List<Float>> buildVectorFromResponse(MLOutput mlOutput) {
         for (final ModelTensors tensors : tensorOutputList) {
             final List<ModelTensor> tensorsList = tensors.getMlModelTensors();
             for (final ModelTensor tensor : tensorsList) {
+                String exceptionMessage = EXCEPTION_MESSAGE_MODEL_PROCESSING_FAILED;
+                if (Objects.isNull(tensor.getData())) {
+                    if (Objects.nonNull(tensor.getDataAsMap()) && Strings.isNotBlank((String) tensor.getDataAsMap().get("message"))) {
+                        exceptionMessage = (String) tensor.getDataAsMap().get("message");
+                    }
+                    throw new IllegalStateException(exceptionMessage);
+                }
                 vector.add(Arrays.stream(tensor.getData()).map(value -> (Float) value).collect(Collectors.toList()));
             }
         }

diff --git a/src/test/java/org/opensearch/neuralsearch/ml/MLCommonsClientAccessorTests.java b/src/test/java/org/opensearch/neuralsearch/ml/MLCommonsClientAccessorTests.java
@@ -5,6 +5,7 @@
 
 package org.opensearch.neuralsearch.ml;
 
+import static org.mockito.ArgumentMatchers.any;
 import static org.mockito.Mockito.mock;
 import static org.mockito.Mockito.times;
 
@@ -328,6 +329,21 @@ public void testInferenceSentencesMultimodal_whenNodeNotConnectedException_thenR
         Mockito.verify(singleSentenceResultListener).onFailure(nodeNodeConnectedException);
     }
 
+    public void testInferenceMultimodal_whenInvalidInputAndEmptyTensorOutput_thenFail() {
+        Mockito.doAnswer(invocation -> {
+            final ActionListener<MLOutput> actionListener = invocation.getArgument(2);
+            actionListener.onResponse(createEmptyModelTensorOutput());
+            return null;
+        }).when(client).predict(Mockito.eq(TestCommonConstants.MODEL_ID), Mockito.isA(MLInput.class), Mockito.isA(ActionListener.class));
+
+        accessor.inferenceSentences(TestCommonConstants.MODEL_ID, TestCommonConstants.SENTENCES_MAP, singleSentenceResultListener);
+
+        Mockito.verify(client)
+            .predict(Mockito.eq(TestCommonConstants.MODEL_ID), Mockito.isA(MLInput.class), Mockito.isA(ActionListener.class));
+        Mockito.verify(singleSentenceResultListener).onFailure(any());
+        Mockito.verifyNoMoreInteractions(singleSentenceResultListener);
+    }
+
     private ModelTensorOutput createModelTensorOutput(final Float[] output) {
         final List<ModelTensors> tensorsList = new ArrayList<>();
         final List<ModelTensor> mlModelTensorList = new ArrayList<>();
@@ -355,4 +371,22 @@ private ModelTensorOutput createModelTensorOutput(final Map<String, String> map)
         tensorsList.add(modelTensors);
         return new ModelTensorOutput(tensorsList);
     }
+
+    private ModelTensorOutput createEmptyModelTensorOutput() {
+        final List<ModelTensors> tensorsList = new ArrayList<>();
+        final List<ModelTensor> mlModelTensorList = new ArrayList<>();
+        final ModelTensor tensor = new ModelTensor(
+            "someValue",
+            null,
+            new long[] { 1, 2 },
+            MLResultDataType.FLOAT64,
+            ByteBuffer.wrap(new byte[12]),
+            "mockResult",
+            ImmutableMap.of("message", "The system encountered an unexpected error during processing. Try your request again.")
+        );
+        mlModelTensorList.add(tensor);
+        final ModelTensors modelTensors = new ModelTensors(mlModelTensorList);
+        tensorsList.add(modelTensors);
+        return new ModelTensorOutput(tensorsList);
+    }
 }