Fixed error for case when mltensor has data as null (opensearch-proje…

…ct#404) * Fixed error for case when mltensor has data as null Signed-off-by: Martin Gaievski <[email protected]> * Changed error message handling Signed-off-by: Martin Gaievski <[email protected]> --------- Signed-off-by: Martin Gaievski <[email protected]>
junqiu-lei · Oct 6, 2023 · 47d1aee · 47d1aee
1 parent bc6ac7a
commit 47d1aee
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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
@@ -11,13 +11,16 @@
 import java.util.ArrayList;
 import java.util.Arrays;
 import java.util.List;
+import java.util.Locale;
 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 +43,8 @@
 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_PREDICT_FAILED = "failed while calling model, check error log for details";
+    private static final String EXCEPTION_MESSAGE_PREFIX_MODEL_PREDICT_FAILED = "encountered following error while calling a model";
 
     /**
      * Wrapper around {@link #inferenceSentences} that expected a single input text and produces a single floating
@@ -187,6 +192,20 @@ private List<List<Float>> buildVectorFromResponse(MLOutput mlOutput) {
         for (final ModelTensors tensors : tensorOutputList) {
             final List<ModelTensor> tensorsList = tensors.getMlModelTensors();
             for (final ModelTensor tensor : tensorsList) {
+                if (Objects.isNull(tensor.getData())) {
+                    if (Objects.nonNull(tensor.getDataAsMap()) && Strings.isNotBlank((String) tensor.getDataAsMap().get("message"))) {
+                        String errorFromModel = (String) tensor.getDataAsMap().get("message");
+                        throw new IllegalStateException(
+                            String.format(Locale.ROOT, "%s: %s", EXCEPTION_MESSAGE_PREFIX_MODEL_PREDICT_FAILED, errorFromModel)
+                        );
+                    } else {
+                        log.error(
+                            "Received following output tensor from a model, there is no detailed error message: {}",
+                            tensor.toString()
+                        );
+                        throw new IllegalStateException(EXCEPTION_MESSAGE_MODEL_PREDICT_FAILED);
+                    }
+                }
                 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 +5,8 @@
 
 package org.opensearch.neuralsearch.ml;
 
+import static org.mockito.ArgumentMatchers.any;
+import static org.mockito.Mockito.clearInvocations;
 import static org.mockito.Mockito.mock;
 import static org.mockito.Mockito.times;
 
@@ -328,6 +330,65 @@ public void testInferenceSentencesMultimodal_whenNodeNotConnectedException_thenR
         Mockito.verify(singleSentenceResultListener).onFailure(nodeNodeConnectedException);
     }
 
+    public void testInferenceMultimodal_whenInvalidInputAndEmptyTensorOutput_thenFail() {
+        List<ModelTensors> tensorsList = new ArrayList<>();
+        List<ModelTensor> mlModelTensorList = List.of(
+            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.")
+            )
+        );
+        final ModelTensors modelTensors = new ModelTensors(mlModelTensorList);
+        ModelTensorOutput outputWithErrorMessage = new ModelTensorOutput(List.of(modelTensors));
+
+        Mockito.doAnswer(invocation -> {
+            final ActionListener<MLOutput> actionListener = invocation.getArgument(2);
+            actionListener.onResponse(outputWithErrorMessage);
+            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);
+
+        clearInvocations(client, singleSentenceResultListener);
+
+        List<ModelTensor> mlModelTensorList2 = List.of(
+            new ModelTensor(
+                "someValue",
+                null,
+                new long[] { 1, 2 },
+                MLResultDataType.FLOAT64,
+                ByteBuffer.wrap(new byte[12]),
+                "mockResult",
+                ImmutableMap.of("test_key", "test_value")
+            )
+        );
+        final ModelTensors modelTensors2 = new ModelTensors(mlModelTensorList2);
+        ModelTensorOutput outputWithErrorMessage2 = new ModelTensorOutput(List.of(modelTensors2));
+
+        Mockito.doAnswer(invocation -> {
+            final ActionListener<MLOutput> actionListener = invocation.getArgument(2);
+            actionListener.onResponse(outputWithErrorMessage2);
+            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<>();