ChatGPT와 Java를 사용하여 지능형 추천 시스템을 개발하는 방법

import java.io.*;
import java.net.*;

public class ChatServer {
    public static void main(String[] args) throws IOException {
        ServerSocket serverSocket = new ServerSocket(9999);
        
        Socket clientSocket = serverSocket.accept();
        BufferedReader in = new BufferedReader(new InputStreamReader(clientSocket.getInputStream()));
        PrintWriter out = new PrintWriter(clientSocket.getOutputStream(), true);
        
        String inputLine;
        while ((inputLine = in.readLine()) != null) {
            // 调用ChatGPT模型生成回复
            String reply = generateReply(inputLine);
            
            out.println(reply);
        }
    }
    
    private static String generateReply(String input) {
        // 调用ChatGPT模型生成回复的代码
        // ...
        return "这是ChatGPT生成的回复";
    }
}

import ai.openai.gpt.*;

public class ChatServer {
    // ...
    
    private static String generateReply(String input) {
        Model model = Model.builder()
            .architecture(Architecture.GPT2)
            .modelDirectory(new File("/path/to/model"))  // ChatGPT模型的路径
            .tokenizer(Tokenization.REGEX)  // 根据需要选择合适的分词器
            .build();
            
        CompletionResult completionResult = model
            .complete(input, CompletionPrompt.builder().build(), 3, 10);
            
        return completionResult.getChoices().get(0).getText();
    }
}

import ai.openai.gpt.*;

public class ChatServer {
    // ...
    
    private static String generateReply(String input) {
        // 根据用户的输入和ChatGPT生成的回复获取用户的需求
        String userRequest = extractUserRequest(input);
        
        // 根据用户需求调用推荐算法生成推荐结果
        List<String> recommendedItems = getRecommendedItems(userRequest);
        
        // 返回推荐结果
        return "这是ChatGPT生成的回复，" + recommendedItems.toString();
    }
    
    private static String extractUserRequest(String input) {
        // 根据ChatGPT生成的回复提取用户的需求
        // ...
        return "用户需求";
    }
    
    private static List<String> getRecommendedItems(String userRequest) {
        // 使用推荐算法根据用户需求生成推荐结果
        // ...
        return List.of("推荐结果1", "推荐结果2", "推荐结果3");
    }
}