Implementing ChatGPT with Spring Boot: A Complete Example

Introduction:
Chatbots have revolutionized the way businesses interact with their customers. Spring Boot, a popular Java framework, provides a robust platform for building web applications, including chatbot implementations. In this blog post, we will explore the implementation of ChatGPT, a powerful language model developed by OpenAI, using Spring Boot. By combining the capabilities of Spring Boot and ChatGPT, we can create intelligent and interactive chatbot applications. Let’s dive into a complete example to showcase the implementation.

Setting Up the Project:
To get started, let’s set up a Spring Boot project and configure the necessary dependencies. Follow these steps:

Step 1: Create a new Spring Boot project using your preferred IDE or the Spring Initializr.
Step 2: Add the required dependencies to your project’s build file (e.g., Maven or Gradle). Include the necessary Spring Boot starter dependencies and the OpenAI GPT dependency:

<!-- Spring Boot dependencies -->
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-web</artifactId>
</dependency>

<!-- OpenAI GPT dependency -->
<dependency>
    <groupId>com.openai</groupId>
    <artifactId>gpt-3.5</artifactId>
    <version>1.0.0</version>
</dependency>

Implementing the ChatGPT Controller:
Next, let’s create a controller that will handle the chatbot’s API endpoints. Add a new class called ChatController to your project and implement the following code:

import com.openai.gpt.GPT;
import com.openai.gpt.GPTCompletionResult;
import com.openai.gpt.GPTFactory;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestBody;
import org.springframework.web.bind.annotation.RestController;

@RestController
public class ChatController {
    @Value("${openai.api.key}")
    private String apiKey;

    @PostMapping("/chat")
    public String chat(@RequestBody String userInput) {
        GPT gpt = GPTFactory.create(apiKey);
        GPTCompletionResult result = gpt.complete(userInput);
        return result.getText();
    }
}

In this example, we use the com.openai.gpt.GPT class from the OpenAI GPT library to create an instance of the language model. The GPTCompletionResult object contains the generated response from the chatbot based on the user’s input. The @PostMapping("/chat") annotation maps the /chat endpoint to the chat() method, which takes the user’s input as a request body and returns the chatbot’s response as a string.

Configuring OpenAI API Key:
To use the OpenAI GPT library, you need to provide your OpenAI API key. Add the following line to your application.properties file:

openai.api.key=YOUR_OPENAI_API_KEY

Make sure to replace YOUR_OPENAI_API_KEY with your actual API key.

Running the Application:
With the project set up and the controller implemented, you can now run your Spring Boot application. Once the application is running, you can start interacting with the chatbot by sending HTTP POST requests to http://localhost:8080/chat with the user’s input in the request body.

Conclusion:
In this blog post, we explored the implementation of ChatGPT using Spring Boot, showcasing how these technologies can be combined to create intelligent and interactive chatbot applications. By leveraging the power of Spring Boot’s web framework and the capabilities of ChatGPT, developers can build sophisticated chat

bot systems with ease. The complete example provided serves as a starting point for developing your own chatbot application using Java and Spring Boot. Happy coding!