How to use ChatGPT and Java to develop an intelligent medical consultation platform

How to use ChatGPT and Java to develop an intelligent medical consultation platform

Introduction:
As people pay more attention to health, the demand for intelligent medical consultation platforms is increasing. Increase. ChatGPT is a powerful natural language processing model provided by OpenAI, which can achieve natural conversations with users. This article will introduce how to develop an intelligent medical consultation platform by combining ChatGPT and Java, and provide specific code examples.

1. Preparation
   First of all, make sure you have the following preparations:
2. Install the Java development environment (JDK)
3. Register an OpenAI account and obtain ChatGPT’s API key
4. Make sure you have a backend server to deploy your application, you can choose to use Spring Boot to simplify the development and deployment process

5. Import related dependencies
   In your Java project, add the following dependencies:

   <dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-web</artifactId>
   </dependency>
   <dependency>
    <groupId>com.google.code.gson</groupId>
    <artifactId>gson</artifactId>
    <version>2.8.7</version>
   </dependency>
   <dependency>
    <groupId>org.apache.httpcomponents</groupId>
    <artifactId>httpclient</artifactId>
    <version>4.5.13</version>
   </dependency>

6. Implementing the call of ChatGPT
   Create a Java class named ChatGPTClient to implement interaction with the ChatGPT API. In this class, we need to implement a method to send the user's input and get the model's reply.

import com.google.gson.Gson;
import org.apache.http.HttpEntity;
import org.apache.http.HttpException;
import org.apache.http.HttpResponse;
import org.apache.http.client.methods.HttpPost;
import org.apache.http.entity.StringEntity;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;

import java.io.IOException;
import java.util.HashMap;
import java.util.Map;

public class ChatGPTClient {
    private String apiKey;
    private String apiUrl = "https://api.openai.com/v1/engines/davinci/completions";

    public ChatGPTClient(String apiKey) {
        this.apiKey = apiKey;
    }

    public String getGPTResponse(String userMessage) throws IOException, HttpException {
        CloseableHttpClient client = HttpClients.createDefault();
        HttpPost httpPost = new HttpPost(apiUrl);
        httpPost.setHeader("Content-Type", "application/json");
        httpPost.setHeader("Authorization", "Bearer " + apiKey);

        // 设置请求参数
        Map<String, String> data = new HashMap<>();
        data.put("prompt", userMessage);
        data.put("max_tokens", "50");

        StringEntity entity = new StringEntity(new Gson().toJson(data));
        httpPost.setEntity(entity);

        // 发送请求 Get response
        HttpResponse response = client.execute(httpPost);
        HttpEntity responseEntity = response.getEntity();
        String responseContent = EntityUtils.toString(responseEntity);

        if (response.getStatusLine().getStatusCode() != 200) {
            throw new HttpException("ChatGPT请求出错，状态码：" + response.getStatusLine().getStatusCode());
        }

        client.close();

        return responseContent;
    }
}

4. Create a Spring Boot-based HTTP interface
   In your Spring Boot project, create a class named ChatController to handle HTTP requests and call ChatGPTClient.

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.*;

import java.io.IOException;

@RestController
@RequestMapping("/api/chat")
public class ChatController {
    @Autowired
    private ChatGPTClient chatGPTClient;

    @PostMapping
    public String chatWithGPT(@RequestBody String userMessage) throws IOException, HttpException {
        return chatGPTClient.getGPTResponse(userMessage);
    }
}

5. Deploy and test your application
   Use Spring Boot tools for Java to package and deploy your application to your server. Make sure your application is started and accessible via the HTTP interface.

You can use Postman or other HTTP request tools to test your application. Send a POST request to the /api/chat interface, and the request body contains the user's input message. You will get the ChatGPT model's reply as an HTTP response.

Summary:
This article introduces how to use ChatGPT and Java to develop an intelligent medical consultation platform. By combining ChatGPT API and Spring Boot, we can implement a medical consultation system with natural language processing capabilities. I hope this article will be helpful to you in developing an intelligent medical consultation platform.

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