Unlocking AI Potential: Experience ChatGPT API with Spring Boot

Unlocking AI Potential: Experience ChatGPT API with Spring Boot

Table of Contents:

1. Introduction
2. Understanding Chat GPT API
3. Setting up the Spring Boot Project
4. Configuring the API Key and Model
5. Implementing the Chat Endpoint
6. Invoking the Chat GPT API
7. Handling Multiple Alternate Responses
8. Running the Application
9. Conclusion

Introduction

Chat GPT is a powerful language model developed by OpenAI that can be used for a variety of tasks, such as chatbot interactions, speech-to-text, and image generation. In this video, we will explore how to use Spring Boot to invoke the Chat GPT API for chat completion. We will be using the Java Community Library provided by OpenAI to simplify the development process.

Understanding Chat GPT API

Before diving into the implementation details, it is important to understand the concepts of the Chat GPT API, including the request and response structures, and various fields that allow us to configure the API according to our preferences. If You are not familiar with these concepts, please refer to my previous video "Understanding Chat GPT API" for a detailed explanation.

Setting up the Spring Boot Project

To begin with, we need to set up a Spring Boot project. You can do this by visiting start.spring.io and generating a Maven project with the necessary dependencies. Once you have downloaded and extracted the project files, open it in your preferred IDE. The project structure should be familiar, with the customary Maven directory structure.

Configuring the API Key and Model

In order to use the Chat GPT API, we need to configure the API key and model. You can obtain your API key from your OpenAI account. Refer to my video "Understanding Chat GPT API" for instructions on how to obtain the API key. Once you have the API key, navigate to the application.properties file in the Spring Boot project and add the properties "openai.model" and "openai.api.key" with their respective values.

Implementing the Chat Endpoint

Next, let's implement the chat endpoint in our Spring Boot application. Create a new Java class called "MyController" and annotate it with the "@RestController" annotation. This class will handle the incoming requests to the "/chat" endpoint.

Invoking the Chat GPT API

To invoke the Chat GPT API, we will use the OpenAI Service provided by the com.theokanning.openai library. Create a new instance of the OpenAI Service and pass the API key as a parameter. We will also create a list of chat messages to hold the conversation history.

Handling Multiple Alternate Responses

The Chat GPT API allows us to specify the number of alternate responses we want it to generate. By default, it returns a single response. However, if you want to explore multiple responses, you can specify the number using the "n" parameter. We will iterate over the choices list and concatenate the response content to a return STRING, separating each response with a new line for readability.

Running the Application

To run the Spring Boot application, click on the run button in your IDE. Make sure to add a new run configuration and specify the main class of your application. Once the application is running, you can access the chat endpoint through your browser using the URL "http://localhost:8080/chat" and provide a prompt for the conversation.

Conclusion

In this video, we learned how to set up a Spring Boot application and invoke the Chat GPT API for chat completion. We explored the use of the OpenAI Java Community Library to simplify the development process. By following the steps outlined in this video, you should now be able to integrate the Chat GPT API into your own Java applications.

How to Use Spring Boot to Invoke Chat GPT API for Chat Completion

Chat GPT is an exceptionally powerful language model developed by OpenAI. It serves a wide array of purposes, including chatbot interactions, speech-to-text conversion, and even image generation. In this article, we will Delve into the process of utilizing Spring Boot to invoke the Chat GPT API in order to achieve chat completion. To streamline the development process, we will be utilizing the Java Community Library provided by OpenAI.

Understanding Chat GPT API

Before diving into the implementation details, it is crucial to grasp the underlying concepts of the Chat GPT API. Familiarize yourself with the intricacies of the request and response structures, as well as the numerous fields that enable you to fine-tune the API according to your preferences. If you require an in-depth explanation, please refer to the video titled "Understanding Chat GPT API".

Setting up the Spring Boot Project

The first step entails setting up a Spring Boot project. Begin by visiting start.spring.io and generating a Maven project, ensuring that you include the necessary dependencies. After downloading and extracting the project files, open your preferred Integrated Development Environment (IDE) and import the project. The directory structure should be organized according to the standard Maven format.

Configuring the API Key and Model

To leverage the Chat GPT API, you must configure the API key and model. The API key can be obtained from your OpenAI account. For instructions on how to acquire the API key, please refer to the video titled "Understanding Chat GPT API". Upon obtaining the API key, navigate to the application.properties file in your Spring Boot project. Add the following properties: "openai.model" and "openai.api.key". Assign the corresponding values to these properties.

Implementing the Chat Endpoint

The next step revolves around implementing the chat endpoint in your Spring Boot application. This involves creating a new Java class, "MyController", and annotating it with the "@RestController" annotation. This class will handle incoming requests to the "/chat" endpoint, allowing for seamless communication with the chatbot.

Invoking the Chat GPT API

To invoke the Chat GPT API, you will need to utilize the OpenAI Service provided by the com.theokanning.openai library. Create a new instance of the OpenAI Service and pass the API key as a parameter. Additionally, create a list of chat messages to store the conversation history.

Handling Multiple Alternate Responses

The Chat GPT API offers the ability to specify the number of alternate responses you desire. By default, it returns a single response. However, if you wish to explore multiple responses, you can utilize the "n" parameter. Iterate over the choices list and concatenate the response content to a return string, ensuring each response is separated by a new line for enhanced readability.

Running the Application

To run the Spring Boot application, simply click on the "run" button within your IDE. Prior to executing the application, be sure to add a new run configuration and specify the main class of your application. Once the application is up and running, you can access the chat endpoint through your web browser using the URL "http://localhost:8080/chat". Provide a prompt to initialize the conversation.

Conclusion

In conclusion, this article has provided an in-depth overview of utilizing Spring Boot to invoke the Chat GPT API for chat completion. By following the outlined steps, you should be equipped with the knowledge and tools necessary to seamlessly integrate the Chat GPT API into your own Java applications.