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Add multi modal default preprocess function
Signed-off-by: zane-neo <zaniu@amazon.com>
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39 changes: 39 additions & 0 deletions
39
...earch/ml/common/connector/functions/preprocess/MultiModalEmbeddingPreProcessFunction.java
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,39 @@ | ||
| /* | ||
| * | ||
| * * Copyright OpenSearch Contributors | ||
| * * SPDX-License-Identifier: Apache-2.0 | ||
| * | ||
| */ | ||
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| package org.opensearch.ml.common.connector.functions.preprocess; | ||
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| import org.opensearch.ml.common.dataset.TextDocsInputDataSet; | ||
| import org.opensearch.ml.common.dataset.remote.RemoteInferenceInputDataSet; | ||
| import org.opensearch.ml.common.input.MLInput; | ||
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| import java.util.Map; | ||
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| import static org.opensearch.ml.common.utils.StringUtils.convertScriptStringToJsonString; | ||
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| public class MultiModalEmbeddingPreProcessFunction extends ConnectorPreProcessFunction { | ||
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| public MultiModalEmbeddingPreProcessFunction() { | ||
| this.returnDirectlyForRemoteInferenceInput = true; | ||
| } | ||
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| @Override | ||
| public void validate(MLInput mlInput) { | ||
| validateTextDocsInput(mlInput); | ||
| } | ||
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| // The input will must have inputText even it's null, input image is optional. | ||
| @Override | ||
| public RemoteInferenceInputDataSet process(MLInput mlInput) { | ||
| TextDocsInputDataSet inputData = (TextDocsInputDataSet) mlInput.getInputDataset(); | ||
| if (inputData.getDocs().size() == 1) { | ||
| return RemoteInferenceInputDataSet.builder().parameters(convertScriptStringToJsonString(Map.of("parameters", Map.of("inputText", inputData.getDocs().get(0))))).build(); | ||
| } else { | ||
| return RemoteInferenceInputDataSet.builder().parameters(convertScriptStringToJsonString(Map.of("parameters", Map.of("inputText", inputData.getDocs().get(0), "inputImage", inputData.getDocs().get(1))))).build(); | ||
| } | ||
| } | ||
| } |
101 changes: 101 additions & 0 deletions
101
...h/ml/common/connector/functions/preprocess/MultiModalEmbeddingPreProcessFunctionTest.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,101 @@ | ||
| /* | ||
| * Copyright OpenSearch Contributors | ||
| * SPDX-License-Identifier: Apache-2.0 | ||
| */ | ||
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| package org.opensearch.ml.common.connector.functions.preprocess; | ||
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| import org.junit.Before; | ||
| import org.junit.Rule; | ||
| import org.junit.Test; | ||
| import org.junit.rules.ExpectedException; | ||
| import org.opensearch.ml.common.FunctionName; | ||
| import org.opensearch.ml.common.dataset.TextDocsInputDataSet; | ||
| import org.opensearch.ml.common.dataset.TextSimilarityInputDataSet; | ||
| import org.opensearch.ml.common.dataset.remote.RemoteInferenceInputDataSet; | ||
| import org.opensearch.ml.common.input.MLInput; | ||
| import org.w3c.dom.Text; | ||
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| import java.rmi.Remote; | ||
| import java.util.ArrayList; | ||
| import java.util.Arrays; | ||
| import java.util.List; | ||
| import java.util.Map; | ||
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| import static org.junit.Assert.assertEquals; | ||
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| public class MultiModalEmbeddingPreProcessFunctionTest { | ||
| @Rule | ||
| public ExpectedException exceptionRule = ExpectedException.none(); | ||
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| MultiModalEmbeddingPreProcessFunction function; | ||
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| TextSimilarityInputDataSet textSimilarityInputDataSet; | ||
| TextDocsInputDataSet textDocsInputDataSet; | ||
| RemoteInferenceInputDataSet remoteInferenceInputDataSet; | ||
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| MLInput textEmbeddingInput; | ||
| MLInput textSimilarityInput; | ||
| MLInput remoteInferenceInput; | ||
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| @Before | ||
| public void setUp() { | ||
| function = new MultiModalEmbeddingPreProcessFunction(); | ||
| textSimilarityInputDataSet = TextSimilarityInputDataSet.builder().queryText("test").textDocs(Arrays.asList("hello")).build(); | ||
| textDocsInputDataSet = TextDocsInputDataSet.builder().docs(Arrays.asList("hello", "world")).build(); | ||
| remoteInferenceInputDataSet = RemoteInferenceInputDataSet.builder().parameters(Map.of("inputText", "value1", "inputImage", "value2")).build(); | ||
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| textEmbeddingInput = MLInput.builder().algorithm(FunctionName.TEXT_EMBEDDING).inputDataset(textDocsInputDataSet).build(); | ||
| textSimilarityInput = MLInput.builder().algorithm(FunctionName.TEXT_SIMILARITY).inputDataset(textSimilarityInputDataSet).build(); | ||
| remoteInferenceInput = MLInput.builder().algorithm(FunctionName.REMOTE).inputDataset(remoteInferenceInputDataSet).build(); | ||
| } | ||
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| @Test | ||
| public void process_NullInput() { | ||
| exceptionRule.expect(IllegalArgumentException.class); | ||
| exceptionRule.expectMessage("Preprocess function input can't be null"); | ||
| function.apply(null); | ||
| } | ||
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| @Test | ||
| public void process_WrongInput() { | ||
| exceptionRule.expect(IllegalArgumentException.class); | ||
| exceptionRule.expectMessage("This pre_process_function can only support TextDocsInputDataSet"); | ||
| function.apply(textSimilarityInput); | ||
| } | ||
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| @Test | ||
| public void process_input_text_image() { | ||
| MLInput mlInput = MLInput.builder().algorithm(FunctionName.TEXT_EMBEDDING).inputDataset(textDocsInputDataSet).build(); | ||
| RemoteInferenceInputDataSet dataSet = function.apply(mlInput); | ||
| assertEquals(2, dataSet.getParameters().size()); | ||
| assertEquals("hello", dataSet.getParameters().get("inputText")); | ||
| assertEquals("world", dataSet.getParameters().get("inputImage")); | ||
| } | ||
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| @Test | ||
| public void process_input_text_only() { | ||
| TextDocsInputDataSet textDocsInputDataSet1 = TextDocsInputDataSet.builder().docs(Arrays.asList("hello")).build(); | ||
| MLInput mlInput = MLInput.builder().algorithm(FunctionName.TEXT_EMBEDDING).inputDataset(textDocsInputDataSet1).build(); | ||
| RemoteInferenceInputDataSet dataSet = function.apply(mlInput); | ||
| assertEquals(1, dataSet.getParameters().size()); | ||
| assertEquals("hello", dataSet.getParameters().get("inputText")); | ||
| } | ||
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| @Test | ||
| public void process_input_text_null() { | ||
| exceptionRule.expect(IllegalArgumentException.class); | ||
| exceptionRule.expectMessage("No input text or image provided"); | ||
| List<String> docs = new ArrayList<>(); | ||
| docs.add(null); | ||
| TextDocsInputDataSet textDocsInputDataSet1 = TextDocsInputDataSet.builder().docs(docs).build(); | ||
| MLInput mlInput = MLInput.builder().algorithm(FunctionName.TEXT_EMBEDDING).inputDataset(textDocsInputDataSet1).build(); | ||
| RemoteInferenceInputDataSet dataSet = function.apply(mlInput); | ||
| } | ||
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| @Test | ||
| public void process_RemoteInferenceInput() { | ||
| RemoteInferenceInputDataSet dataSet = function.apply(remoteInferenceInput); | ||
| assertEquals(remoteInferenceInputDataSet, dataSet); | ||
| } | ||
| } |