ChatGPT Java: How to build an intelligent spelling correction tool

ChatGPT Java: How to build an intelligent spelling correction tool

Introduction:
With the continuous development of artificial intelligence technology, intelligent spelling correction tools have become An important application in daily life. This article will introduce how to use Java to build an intelligent spelling correction tool and provide specific code examples. We will use a method based on the ChatGPT model for spelling correction.

Step One: Preparation

1. Make sure the JDK is installed and the environment variables are configured.
2. Download the ChatGPT model file, which can be obtained from the OpenAI official website or related open source communities.

Step 2: Load the ChatGPT model
Loading the ChatGPT model in Java requires the use of open source libraries such as Deep Java Library (DJL) and DL4J (DeepLearning4j), which provide convenient machine learning models Loading and prediction functions.

First, we need to add the following dependencies in the pom.xml file:

<dependencies>
    <dependency>
        <groupId>ai.djl.tensorflow</groupId>
        <artifactId>tensorflow-engine</artifactId>
        <version>0.18.0</version>
    </dependency>

    <dependency>
        <groupId>ai.djl.tensorflow</groupId>
        <artifactId>tensorflow-engine-api</artifactId>
        <version>0.18.0</version>
    </dependency>

    <dependency>
        <groupId>ai.djl.tensorflow</groupId>
        <artifactId>tensorflow-engine-native</artifactId>
        <version>0.18.0</version>
        <classifier>linux-x86_64-cpu</classifier>
    </dependency>

    <dependency>
        <groupId>ai.djl.tensorflow</groupId>
        <artifactId>tensorflow-engine-native</artifactId>
        <version>0.18.0</version>
        <classifier>macos-x86_64-cpu</classifier>
    </dependency>

    <dependency>
        <groupId>org.nd4j</groupId>
        <artifactId>nd4j-native-platform</artifactId>
        <version>1.0.0-beta7</version>
    </dependency>
</dependencies>

In the Java code, we need to load the ChatGPT model and its configuration:

import ai.djl.*;
import ai.djl.inference.*;
import ai.djl.inference.tensor.*;
import ai.djl.modality.*;
import ai.djl.modality.nlp.*;
import ai.djl.modality.nlp.qa.*;
import ai.djl.modality.nlp.translator.*;
import ai.djl.modality.nlp.vocab.*;
import ai.djl.translate.*;
import ai.djl.util.*;
import java.nio.file.*;
import java.util.*;
import java.util.stream.*;

public class SpellingCorrection {
    private static final String MODEL_PATH = "path/to/chatgpt-model";
    private static final String CONFIG_PATH = "path/to/chatgpt-config.json";
    private static final int MAX_RESULTS = 3;
    
    private Translator<String, String> translator;
    private Predictor<String, String> predictor;
    private Vocabulary vocab;
    
    public SpellingCorrection() throws MalformedModelException, ModelNotFoundException {
        translator = ChatTranslator.builder()
                .addTransform(new Lowercase())
                .optFilter(filters)
                .addTransform(new Tokenize())
                .optFilter(filters)
                .addTransform(new ToTensor())
                .optFilter(filters)
                .addTransform(new Flattern<>(String.class, String.class))
                .optFilter(filters)
                .optPostProcessors(new BeamSearchTranslator(3))
                .build();
        
        Model model = Model.newInstance(MODEL_PATH, DEVICE);
        model.load(Paths.get(CONFIG_PATH), "chatgpt");
        model.setBlock(model.getBlock());
        
        predictor = TranslatorModel.newInstance(model).newPredictor(translator);
        
        vocab = Vocabulary.builder()
                .optMinFrequency(5)
                .addFromTextFile(vocabPath, "\s+")
                .build();
    }
    
    public String correct(String input) throws TranslateException {
        List<String> inputList = Arrays.asList(input.trim().split("\s+"));
        String output = predictor.predict(inputList);
        return output;
    }
}

Step 3: Spelling correction function
When building an intelligent spelling correction tool, we can use a method based on a binary language model: given an input, we can generate possible variants and predict them in the prediction phase Choose the most likely correction. We can use the ChatGPT model to generate possible variants and rank them using the probabilities of the language model.

In Java code, we need to implement a method to generate possible variants:

public List<String> generateVariants(String input) {
    List<String> variants = new ArrayList<>();
    for (int i = 0; i < input.length(); i++) {
        String variant = input.substring(0, i) + input.substring(i + 1);
        variants.add(variant);
    }
    return variants;
}

Then, we can use the ChatGPT model to get the likelihood of each variant and follow the possible Sort in descending order of gender:

public String correct(String input) throws TranslateException {
    List<String> variants = generateVariants(input);
    Map<String, Float> scores = new HashMap<>();
    for (String variant : variants) {
        List<String> inputList = Arrays.asList(variant.trim().split("\s+"));
        String output = predictor.predict(inputList);
        float score = calculateScore(output);
        scores.put(variant, score);
    }
    
    List<String> corrections = scores.entrySet().stream()
            .sorted(Map.Entry.comparingByValue(Comparator.reverseOrder()))
            .limit(MAX_RESULTS)
            .map(Map.Entry::getKey)
            .collect(Collectors.toList());
    
    return corrections.get(0);
}

private float calculateScore(String output) {
    // 计算语言模型的概率作为变体的得分
}

Step 4: Use the spelling correction tool
Finally, we can use this smart spelling correction tool to correct the given input:

public static void main(String[] args) throws MalformedModelException, ModelNotFoundException, TranslateException {
    SpellingCorrection sp = new SpellingCorrection();
    String input = "Hwllo, wrld!";
    String output = sp.correct(input);
    System.out.println("Corrected: " + output);
}

Summary:
In this article, we introduce how to build an intelligent spelling correction tool using Java. By loading the ChatGPT model and using a language model-based approach, we are able to generate possible variants and rank them by likelihood. By providing code examples, we hope readers can apply these techniques in real projects and further optimize and extend the intelligent spelling correction tool.

The above is the detailed content of ChatGPT Java: How to build an intelligent spelling correction tool. For more information, please follow other related articles on the PHP Chinese website!