Learn How to Add a Frontend to Your OpenAI Project

Table of Contents

1. Introduction
2. Building the Backend API
   • Setting up the Express server
   • Sending requests to OpenAI
   • Handling API responses
3. Creating the Front-End Web Page
   • Creating a public folder
   • Using Middleware in Express
   • Adding HTML, CSS, and JavaScript files
4. Implementing Functionality
   • Handling form submissions
   • Sending POST requests to the API
   • Updating the webpage with API responses
5. Conclusion

Building a Front-End Web Page to Interact with the OpenAI API

Now that we have successfully built our backend API to send requests to the OpenAI API and receive AI-generated content, it's time to Create a front-end web page to Interact with this API and display the responses in a browser.

Step 1: Creating a Public Folder

The first thing we need to do is create a public folder to store all the files that will be accessible to the browser, including HTML, CSS, and any other assets like stylesheets or images. This folder will serve as the root directory for our web page.

To tell Express that this folder should be public and accessible to the browser, we need to use middleware. We can use the express.static function to make the public folder available to Express. Simply add the following code to your Express server file:

app.use(express.static('public'));

With this middleware in place, any files inside the public folder will be accessible at the root of the application. For example, if You have an image named logo.png inside the public folder, you can access it in the browser at localhost:4000/logo.png.

Step 2: Adding HTML, CSS, and JavaScript Files

Now that we have set up the public folder, we can add our HTML, CSS, and JavaScript files to create the front-end web page.

Inside the public folder, create an index.html file, a styles.css file, and an index.js file. You can also add any other assets you might need, like images or additional stylesheets.

In the index.html file, you can add the necessary HTML structure for your web page. This will include elements like a navigation bar, form inputs, and elements to display the API responses. Feel free to customize the HTML structure to fit your specific requirements.

In the styles.css file, you can add the necessary CSS rules to style your web page. This could include defining the appearance of elements, setting layout properties, and adding any desired visual effects. Be sure to give your web page a visually appealing and user-friendly design.

In the index.js file, you will write the JavaScript code to handle form submissions and send POST requests to the backend API. This JavaScript code will also update the web page with the API responses, dynamically displaying the generated content to the user.

Step 3: Implementing Functionality

Now that we have the HTML, CSS, and JavaScript files in place, it's time to implement the functionality of our front-end web page.

First, we need to handle form submissions. Add event listeners to both the metadata form and the image form, and specify a function to be called when each form is submitted. Inside these functions, use the preventDefault() method to prevent the default form submission behavior, which would cause the page to refresh.

Next, we want to send POST requests to our backend API when the forms are submitted. Use the fetch() API to make the requests. For the metadata form, send a POST request to the /openAPI/meta endpoint, passing along the value of the input field as the title property in the request body. Remember to set the Content-Type header to application/json.

For the image form, send a POST request to the /openAPI/image endpoint, passing the value of the input field as the prompt property in the request body. Again, don't forget to set the Content-Type header to application/json.

Once we receive the API responses, we can update the web page with the generated content. Get the response data using the response.json() method and extract the Relevant information, such as the description, tags, and image URL.

Update the respective elements in the web page's HTML with the received information. For example, set the textContent property of the description element to the received description, and set the src attribute of the image element to the received image URL.

Conclusion

In this article, we learned how to create a front-end web page to interact with the OpenAI API and display the AI-generated content in a browser. We discussed the steps involved in setting up a public folder, adding HTML, CSS, and JavaScript files, and implementing the necessary functionality to send POST requests to the backend API and update the web page with the API responses.

By following these steps, you can create a user-friendly web page that seamlessly interacts with the OpenAI API and provides an intuitive interface for users to generate AI content.

Remember to test your web page thoroughly and handle any error cases that may arise while making API requests or handling responses. With careful implementation and thoughtful design, you can create a powerful and engaging web page that leverages the power of AI to enhance user experiences and provide valuable content.