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[api] Support "inputs" key in json request for text embedding translator #3083

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Apr 15, 2024
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[api] Support "inputs" key in json request for text embedding translator #3083

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94 changes: 94 additions & 0 deletions api/src/main/java/ai/djl/modality/nlp/TextPrompt.java
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@@ -0,0 +1,94 @@
/*
* Copyright 2024 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance
* with the License. A copy of the License is located at
*
* http://aws.amazon.com/apache2.0/
*
* or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES
* OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
* and limitations under the License.
*/
package ai.djl.modality.nlp;

import ai.djl.modality.Input;
import ai.djl.translate.TranslateException;
import ai.djl.util.JsonUtils;

import com.google.gson.JsonElement;
import com.google.gson.JsonParseException;

/** The input container for NLP text prompt. */
public final class TextPrompt {

private String text;
private String[] batch;

private TextPrompt(String text) {
this.text = text;
}

private TextPrompt(String[] batch) {
this.batch = batch;
}

/**
* Returns if the prompt is a batch.
*
* @return {@code true} if the prompt is a batch
*/
public boolean isBatch() {
return batch != null;
}

/**
* Returns the single prompt.
*
* @return the single prompt
*/
public String getText() {
return text;
}

/**
* Returns the batch prompt.
*
* @return the batch prompt
*/
public String[] getBatch() {
return batch;
}

/**
* Returns the {@code TextPrompt} from the {@link Input}.
*
* @param input the input object
* @return the {@code TextPrompt} from the {@link Input}
* @throws TranslateException if the input is invalid
*/
public static TextPrompt parseInput(Input input) throws TranslateException {
String contentType = input.getProperty("Content-Type", null);
String text = input.getData().getAsString();
if (!"application/json".equals(contentType)) {
return new TextPrompt(text);
}

try {
JsonElement element = JsonUtils.GSON.fromJson(text, JsonElement.class);
if (element != null && element.isJsonObject()) {
element = element.getAsJsonObject().get("inputs");
}
if (element == null) {
throw new TranslateException("Missing \"inputs\" in json.");
} else if (element.isJsonArray()) {
String[] batch = JsonUtils.GSON.fromJson(element, String[].class);
return new TextPrompt(batch);
} else {
return new TextPrompt(element.getAsString());
}
} catch (JsonParseException e) {
throw new TranslateException("Input is not a valid json.", e);
}
}
}
13 changes: 6 additions & 7 deletions api/src/main/java/ai/djl/modality/nlp/translator/TextClassificationServingTranslator.java
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Expand Up @@ -15,14 +15,14 @@
import ai.djl.modality.Classifications;
import ai.djl.modality.Input;
import ai.djl.modality.Output;
import ai.djl.modality.nlp.TextPrompt;
import ai.djl.ndarray.BytesSupplier;
import ai.djl.ndarray.NDList;
import ai.djl.translate.Batchifier;
import ai.djl.translate.NoBatchifyTranslator;
import ai.djl.translate.TranslateException;
import ai.djl.translate.Translator;
import ai.djl.translate.TranslatorContext;
import ai.djl.util.JsonUtils;

/**
* A {@link Translator} that can handle generic text classification {@link Input} and {@link
Expand Down Expand Up @@ -57,14 +57,13 @@ public NDList processInput(TranslatorContext ctx, Input input) throws Exception
throw new TranslateException("Input data is empty.");
}

String contentType = input.getProperty("Content-Type", null);
String text = input.getData().getAsString();
if ("application/json".equals(contentType)) {
TextPrompt prompt = TextPrompt.parseInput(input);
if (prompt.isBatch()) {
ctx.setAttachment("batch", Boolean.TRUE);
String[] inputs = JsonUtils.GSON.fromJson(text, String[].class);
return batchTranslator.processInput(ctx, inputs);
return batchTranslator.processInput(ctx, prompt.getBatch());
}
NDList ret = translator.processInput(ctx, text);

NDList ret = translator.processInput(ctx, prompt.getText());
Batchifier batchifier = translator.getBatchifier();
if (batchifier != null) {
NDList[] batch = {ret};
Expand Down
13 changes: 6 additions & 7 deletions api/src/main/java/ai/djl/modality/nlp/translator/TextEmbeddingServingTranslator.java
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Expand Up @@ -14,14 +14,14 @@

import ai.djl.modality.Input;
import ai.djl.modality.Output;
import ai.djl.modality.nlp.TextPrompt;
import ai.djl.ndarray.BytesSupplier;
import ai.djl.ndarray.NDList;
import ai.djl.translate.Batchifier;
import ai.djl.translate.NoBatchifyTranslator;
import ai.djl.translate.TranslateException;
import ai.djl.translate.Translator;
import ai.djl.translate.TranslatorContext;
import ai.djl.util.JsonUtils;

/** A {@link Translator} that can handle generic text embedding {@link Input} and {@link Output}. */
public class TextEmbeddingServingTranslator implements NoBatchifyTranslator<Input, Output> {
Expand Down Expand Up @@ -53,14 +53,13 @@ public NDList processInput(TranslatorContext ctx, Input input) throws Exception
throw new TranslateException("Input data is empty.");
}

String contentType = input.getProperty("Content-Type", null);
String text = input.getData().getAsString();
if ("application/json".equals(contentType)) {
TextPrompt prompt = TextPrompt.parseInput(input);
if (prompt.isBatch()) {
ctx.setAttachment("batch", Boolean.TRUE);
String[] inputs = JsonUtils.GSON.fromJson(text, String[].class);
return batchTranslator.processInput(ctx, inputs);
return batchTranslator.processInput(ctx, prompt.getBatch());
}
NDList ret = translator.processInput(ctx, text);

NDList ret = translator.processInput(ctx, prompt.getText());
Batchifier batchifier = translator.getBatchifier();
if (batchifier != null) {
NDList[] batch = {ret};
Expand Down
13 changes: 6 additions & 7 deletions api/src/main/java/ai/djl/modality/nlp/translator/TokenClassificationServingTranslator.java
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Expand Up @@ -14,14 +14,14 @@

import ai.djl.modality.Input;
import ai.djl.modality.Output;
import ai.djl.modality.nlp.TextPrompt;
import ai.djl.ndarray.BytesSupplier;
import ai.djl.ndarray.NDList;
import ai.djl.translate.Batchifier;
import ai.djl.translate.NoBatchifyTranslator;
import ai.djl.translate.TranslateException;
import ai.djl.translate.Translator;
import ai.djl.translate.TranslatorContext;
import ai.djl.util.JsonUtils;

/**
* A {@link Translator} that can handle generic token classification {@link Input} and {@link
Expand Down Expand Up @@ -56,14 +56,13 @@ public NDList processInput(TranslatorContext ctx, Input input) throws Exception
throw new TranslateException("Input data is empty.");
}

String contentType = input.getProperty("Content-Type", null);
String text = input.getData().getAsString();
if ("application/json".equals(contentType)) {
TextPrompt prompt = TextPrompt.parseInput(input);
if (prompt.isBatch()) {
ctx.setAttachment("batch", Boolean.TRUE);
String[] inputs = JsonUtils.GSON.fromJson(text, String[].class);
return batchTranslator.processInput(ctx, inputs);
return batchTranslator.processInput(ctx, prompt.getBatch());
}
NDList ret = translator.processInput(ctx, text);

NDList ret = translator.processInput(ctx, prompt.getText());
Batchifier batchifier = translator.getBatchifier();
if (batchifier != null) {
NDList[] batch = {ret};
Expand Down
36 changes: 36 additions & 0 deletions ...s/tokenizers/src/test/java/ai/djl/huggingface/tokenizers/TextEmbeddingTranslatorTest.java
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Expand Up @@ -157,6 +157,16 @@ public void testTextEmbeddingTranslator()
float[] res = JsonUtils.GSON.fromJson(out.getAsString(0), float[].class);
Assert.assertEquals(res.length, 384);
Assertions.assertAlmostEquals(res[0], 0.05103);

input = new Input();
Map<String, String> map = new HashMap<>();
map.put("inputs", text);
input.add(JsonUtils.GSON.toJson(map));
input.addProperty("Content-Type", "application/json");
out = predictor.predict(input);
res = (float[]) out.getData().getAsObject();
Assert.assertEquals(res.length, 384);
Assertions.assertAlmostEquals(res[0], 0.05103);
}

try (Model model = Model.newInstance("test")) {
Expand Down Expand Up @@ -237,6 +247,32 @@ public void testTextEmbeddingBatchTranslator()
float[][] res = (float[][]) out.getData().getAsObject();
Assert.assertEquals(res[0].length, 384);
Assertions.assertAlmostEquals(res[0][0], 0.05103);

input = new Input();
Map<String, String[]> map = new HashMap<>();
map.put("inputs", text);
input.add(JsonUtils.GSON.toJson(map));
input.addProperty("Content-Type", "application/json");
out = predictor.predict(input);
res = (float[][]) out.getData().getAsObject();
Assert.assertEquals(res[0].length, 384);
Assertions.assertAlmostEquals(res[0][0], 0.05103);

Assert.assertThrows(
() -> {
Input empty = new Input();
empty.add(JsonUtils.GSON.toJson(new HashMap<>()));
empty.addProperty("Content-Type", "application/json");
predictor.predict(empty);
});

Assert.assertThrows(
() -> {
Input empty = new Input();
empty.add("{ \"invalid json\"");
empty.addProperty("Content-Type", "application/json");
predictor.predict(empty);
});
}
}
}
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