Build an Incredible Full-Stack App with React, OpenAI, and GPT-3!

Build an Incredible Full-Stack App with React, OpenAI, and GPT-3!

Table of Contents:

1. Introduction
2. Setting Up the Backend
   • Initializing the Backend
   • Installing Packages
3. Setting Up the API Key
   • Getting the API Key
   • Configuring the Backend
4. Interacting with the Open AI API
   • Creating an Asynchronous Function
   • Retrieving Data from the API
5. Setting Up Dolly
   • Incorporating Dolly Example Code
   • Testing Dolly
6. Setting Up the Express Server
   • Installing Dependencies
   • Setting Up Endpoints
   • Testing the Server
7. Setting Up the Front End
   • Writing JSX
   • Handling User Input
   • Displaying Output
8. Integrating Tailwind CSS
   • Installing Tailwind CSS
   • Configuring Tailwind
   • Adding CSS Directives
9. Adding Logic to the Component
   • Installing Axios
   • Setting Up Hooks
   • Handling Form Submission
   • Handling Errors
10. Conclusion

Building a Full Stack Application with Open AI API and Dolly

Introduction

In this series, I will Show You how to build a full stack application leveraging the Open AI API. We will be integrating Dolly and GPT on the backend using Node.js and Express, and React on the front end. The goal is to Create an application that allows users to search images and retrieve information using natural language queries.

Setting Up the Backend

To begin, we need to set up the backend by initializing the backend folder and installing the necessary packages. Install Express and bodyParser, as well as the Open AI and Dot EnV packages. Next, create the front-end folder and use "npx create react-app" to generate a React App called "openAIgui". Finally, create a .env and index.js file in the backend folder.

Setting Up the API Key

To access the Open AI API, we first need to obtain the API key. Sign up or log in to the Open AI Website and navigate to the API link. Click on "View API Keys," create a new secret, and copy the key. Open the .env file in the backend folder and set the Open AI API key.

Interacting with the Open AI API

Now that we have the API key set up, we can start interacting with the Open AI API. Go to the Open AI Website's examples section and choose the desired example code, such as "Summarize for a Second Grader". Wrap the code in an asynchronous function called "promptAI" and require the necessary packages. Retrieve the data and prompt the API with the user's query. Replace the hardcoded text with the user's prompt. Test the function to ensure it is working as expected.

Setting Up Dolly

Similarly, we can set up Dolly by retrieving the example code from the Open AI website. Create a function called "promptDolly" and set it up with its own endpoint. Change the prompt in the example code to the user's input. Test the function to see the results.

Setting Up the Express Server

To set up the Express server, require Express, bodyParser, and set up CORS to allow interactions with the front end. Initialize Express and bodyParser, and listen for requests on port 4000. Set up endpoints for both the GPT and Dolly functions, retrieving the user's query from the front end. Test the endpoints using a tool like Thunderclient in VS Code.

Setting Up the Front End

In the front end, write the JSX code. Create a wrapper that centers the content on the screen and set the title as "Open AI". Build a form that handles user input, including a text input field and a select box to toggle between GPT and Dolly. Add a button to submit the form and an output field to display the results. Save the file and test the application by entering queries.

Integrating Tailwind CSS

To enhance the styling of the application, integrate Tailwind CSS. Follow the documentation to install Tailwind CSS and configure it. Add the necessary CSS directives within the index.css file. Run the application, and Tailwind CSS will be applied.

Adding Logic to the Component

To add logic to the component, install the Axios library. Set up hooks for input, output, and endpoints. Create a function to handle form submission and make a post request to the backend API. Depending on the response, render an image or text. Handle errors by logging them.

Conclusion

In this series, we have learned how to build a full stack application using the Open AI API and Dolly. By leveraging the power of natural language processing and image generation, we have created a user-friendly application. Tailwind CSS was integrated to improve the application's visual appeal. With the help of Axios, we were able to Interact with the backend and retrieve information from the Open AI API. This project is just a starting point, and you can customize and expand upon it according to your needs. Enjoy experimenting and exploring the possibilities of AI-powered applications.

Highlights:

• Learn how to build a full stack application with Open AI API and Dolly
• Set up the backend using Node.js and Express
• Interact with the Open AI API to retrieve information
• Incorporate Dolly for image generation
• Set up endpoints and handle user inputs in the front end
• Style the application using Tailwind CSS
• Handle form submissions with logic and error handling

FAQ:

Q: What technologies are used in this project? A: This project uses Node.js, Express, React, Open AI API, and Dolly.

Q: Can I use a different CSS framework instead of Tailwind CSS? A: Yes, you can use any CSS framework of your choice or style the application using plain CSS.

Q: How can I test the application? A: You can use tools like Thunderclient or Postman to test the API endpoints and interact with the application.

Q: Can I add more functionalities to the application? A: Absolutely! This project provides a starting point, and you can customize and expand upon it according to your requirements. Feel free to add more features and experiment with the Open AI API.

Q: Do I need to have prior experience with AI or machine learning to use Open AI API? A: No, you don't need extensive knowledge of AI or machine learning to use the Open AI API. The API provides simplified access to powerful AI capabilities, allowing developers to leverage its functionalities without in-depth expertise in the field.