ChatGPT Java: Bagaimana untuk membina alat pembetulan ejaan pintar

<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>

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;
    }
}

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;
}