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Fix user defined preprocess function missing prediction issue (#2418) (…
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…#2426)

* Fix user defined preprocess function missing prediction issue

Signed-off-by: zane-neo <[email protected]>

* Add validation to predictAction in connector

Signed-off-by: zane-neo <[email protected]>

* Add check to multi-modal non image case

Signed-off-by: zane-neo <[email protected]>

* add UTs

Signed-off-by: zane-neo <[email protected]>

* format code

Signed-off-by: zane-neo <[email protected]>

---------

Signed-off-by: zane-neo <[email protected]>
(cherry picked from commit 89f23d2)

Co-authored-by: zane-neo <[email protected]>
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@opensearch-trigger-bot @zane-neo
opensearch-trigger-bot[bot] and zane-neo authored May 9, 2024
1 parent b7466d5 commit b8d1876
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12 changes: 12 additions & 0 deletions ...hms/src/main/java/org/opensearch/ml/engine/algorithms/remote/RemoteConnectorExecutor.java
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Expand Up @@ -11,6 +11,7 @@
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.atomic.AtomicReference;
Expand All @@ -27,6 +28,8 @@
import org.opensearch.core.xcontent.NamedXContentRegistry;
import org.opensearch.ml.common.FunctionName;
import org.opensearch.ml.common.connector.Connector;
import org.opensearch.ml.common.connector.ConnectorAction;
import org.opensearch.ml.common.connector.MLPreProcessFunction;
import org.opensearch.ml.common.dataset.MLInputDataset;
import org.opensearch.ml.common.dataset.TextDocsInputDataSet;
import org.opensearch.ml.common.dataset.remote.RemoteInferenceInputDataSet;
Expand Down Expand Up @@ -99,6 +102,15 @@ private Tuple<Integer, Integer> calculateChunkSize(TextDocsInputDataSet textDocs
return Tuple.tuple(textDocsLength / stepSize + 1, stepSize);
}
} else {
Optional<ConnectorAction> predictAction = getConnector().findPredictAction();
if (predictAction.isEmpty()) {
throw new IllegalArgumentException("no predict action found");
}
String preProcessFunction = predictAction.get().getPreProcessFunction();
if (preProcessFunction != null && !MLPreProcessFunction.contains(preProcessFunction)) {
// user defined preprocess script, this case, the chunk size is always equals to text docs length.
return Tuple.tuple(textDocsLength, 1);
}
// consider as batch.
return Tuple.tuple(1, textDocsLength);
}
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84 changes: 84 additions & 0 deletions ...ms/src/test/java/org/opensearch/ml/engine/algorithms/remote/AwsConnectorExecutorTest.java
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Expand Up @@ -6,6 +6,7 @@
package org.opensearch.ml.engine.algorithms.remote;

import static org.junit.Assert.assertEquals;
import static org.mockito.ArgumentMatchers.any;
import static org.mockito.Mockito.spy;
import static org.mockito.Mockito.times;
import static org.mockito.Mockito.when;
Expand All @@ -30,6 +31,7 @@
import org.opensearch.common.settings.Settings;
import org.opensearch.common.util.concurrent.ThreadContext;
import org.opensearch.core.action.ActionListener;
import org.opensearch.ingest.TestTemplateService;
import org.opensearch.ml.common.FunctionName;
import org.opensearch.ml.common.connector.AwsConnector;
import org.opensearch.ml.common.connector.Connector;
Expand All @@ -42,6 +44,7 @@
import org.opensearch.ml.common.transport.MLTaskResponse;
import org.opensearch.ml.engine.encryptor.Encryptor;
import org.opensearch.ml.engine.encryptor.EncryptorImpl;
import org.opensearch.script.ScriptService;
import org.opensearch.threadpool.ThreadPool;

import com.google.common.collect.ImmutableList;
Expand All @@ -67,10 +70,15 @@ public class AwsConnectorExecutorTest {

Encryptor encryptor;

@Mock
private ScriptService scriptService;

@Before
public void setUp() {
MockitoAnnotations.openMocks(this);
encryptor = new EncryptorImpl("m+dWmfmnNRiNlOdej/QelEkvMTyH//frS2TBeS2BP4w=");
when(scriptService.compile(any(), any()))
.then(invocation -> new TestTemplateService.MockTemplateScript.Factory("{\"result\": \"hello world\"}"));
}

@Test
Expand Down Expand Up @@ -282,4 +290,80 @@ public void executePredict_RemoteInferenceInput_negativeStepSize_throwIllegalArg
Mockito.verify(actionListener, times(1)).onFailure(exceptionCaptor.capture());
assert exceptionCaptor.getValue() instanceof IllegalArgumentException;
}

@Test
public void executePredict_TextDocsInferenceInput_withoutStepSize_emptyPredictionAction() {
ConnectorAction predictAction = ConnectorAction
.builder()
.actionType(ConnectorAction.ActionType.PREDICT)
.method("POST")
.url("http://openai.com/mock")
.requestBody("{\"input\": ${parameters.input}}")
.preProcessFunction(MLPreProcessFunction.TEXT_DOCS_TO_OPENAI_EMBEDDING_INPUT)
.build();
Map<String, String> credential = ImmutableMap
.of(ACCESS_KEY_FIELD, encryptor.encrypt("test_key"), SECRET_KEY_FIELD, encryptor.encrypt("test_secret_key"));
Map<String, String> parameters = ImmutableMap.of(REGION_FIELD, "us-west-2", SERVICE_NAME_FIELD, "sagemaker");
Connector connector = AwsConnector
.awsConnectorBuilder()
.name("test connector")
.version("1")
.protocol("http")
.parameters(parameters)
.credential(credential)
.build();
connector.decrypt((c) -> encryptor.decrypt(c));
AwsConnectorExecutor executor = spy(new AwsConnectorExecutor(connector));
Settings settings = Settings.builder().build();
threadContext = new ThreadContext(settings);
when(executor.getClient()).thenReturn(client);
when(client.threadPool()).thenReturn(threadPool);
when(threadPool.getThreadContext()).thenReturn(threadContext);

MLInputDataset inputDataSet = TextDocsInputDataSet.builder().docs(ImmutableList.of("input1", "input2", "input3")).build();
executor
.executePredict(MLInput.builder().algorithm(FunctionName.TEXT_EMBEDDING).inputDataset(inputDataSet).build(), actionListener);
ArgumentCaptor<Exception> exceptionArgumentCaptor = ArgumentCaptor.forClass(Exception.class);
Mockito.verify(actionListener, times(1)).onFailure(exceptionArgumentCaptor.capture());
assert exceptionArgumentCaptor.getValue() instanceof IllegalArgumentException;
assert "no predict action found".equals(exceptionArgumentCaptor.getValue().getMessage());
}

@Test
public void executePredict_TextDocsInferenceInput_withoutStepSize_userDefinedPreProcessFunction() {
ConnectorAction predictAction = ConnectorAction
.builder()
.actionType(ConnectorAction.ActionType.PREDICT)
.method("POST")
.url("http://openai.com/mock")
.requestBody("{\"input\": ${parameters.input}}")
.preProcessFunction(
"\n StringBuilder builder = new StringBuilder();\n builder.append(\"\\\"\");\n String first = params.text_docs[0];\n builder.append(first);\n builder.append(\"\\\"\");\n def parameters = \"{\" +\"\\\"text_inputs\\\":\" + builder + \"}\";\n return \"{\" +\"\\\"parameters\\\":\" + parameters + \"}\";"
)
.build();
Map<String, String> credential = ImmutableMap
.of(ACCESS_KEY_FIELD, encryptor.encrypt("test_key"), SECRET_KEY_FIELD, encryptor.encrypt("test_secret_key"));
Map<String, String> parameters = ImmutableMap.of(REGION_FIELD, "us-west-2", SERVICE_NAME_FIELD, "sagemaker");
Connector connector = AwsConnector
.awsConnectorBuilder()
.name("test connector")
.version("1")
.protocol("http")
.parameters(parameters)
.credential(credential)
.actions(Arrays.asList(predictAction))
.build();
connector.decrypt((c) -> encryptor.decrypt(c));
AwsConnectorExecutor executor = spy(new AwsConnectorExecutor(connector));
Settings settings = Settings.builder().build();
threadContext = new ThreadContext(settings);
when(executor.getClient()).thenReturn(client);
when(client.threadPool()).thenReturn(threadPool);
when(threadPool.getThreadContext()).thenReturn(threadContext);
when(executor.getScriptService()).thenReturn(scriptService);

MLInputDataset inputDataSet = TextDocsInputDataSet.builder().docs(ImmutableList.of("input1", "input2", "input3")).build();
executor
.executePredict(MLInput.builder().algorithm(FunctionName.TEXT_EMBEDDING).inputDataset(inputDataSet).build(), actionListener);
}
}

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