Advanced AI assistants like ChatGPT, Bind AI, and others can now fully generate and deploy web applications from simple NLP prompts. Thanks to LLMs like Claude 3.5 Sonnet, GPT-o1, and GPT-4o, users can create anything from simple usernames or blog idea spawners to complex AI image generators or chatbots (an example of which we see later in the article). But what does the process look like? Is it too hard? Is it too expensive? Well, not exactly; we’ll show you how.
This blog will tell you everything you need to know to start creating your own web applications using AI. We’ll show you how AI-powered web applications work, the general steps for creating your AI web apps, and a real-world example of how to code and deploy your web application using Bind AI.
How AI-powered Web Applications Work
AI-powered web applications integrate AI-generated code and user APIs (depending on the app) into web interfaces to create functional applications. They process user inputs through neural networks, analyze real-time data, and generate intelligent responses – text, image, or something else. Several branches of AI can be applied to web applications:
| Branch | Description |
| Machine Learning (ML) | Algorithms that allow systems to learn from data and improve over time. |
| Natural Language Processing (NLP) | Enables machines to understand and respond to human language, including speech and text. |
| Computer Vision | The ability of a machine to interpret and make decisions based on visual data. |
| Reinforcement Learning | A type of machine learning where an agent learns by interacting with its environment and receiving feedback. |
AI integration into web apps involves the front end (what the user interacts with) and the back end (the server side, where AI models are trained or predictions are made). Generally, the front end of AI-powered apps uses HTML and CSS, while the back end is handled by more complex languages like Python and JavaScript.
General Steps to Create an AI-powered Web Application
While we have included a detailed case study on a chatbot, coded and deployed solely using Bind AI, here are the general steps for those who want to be more creative and try it out themself:
1. Head over to Bind AI Copilot and select your model.
2. If you don’t already have something in your mind, identify the type of web application you want to build. Examples can include anything from a basic calculator, username generator, or customer support chatbot to a complex AI image generator or your version of ChatGPT.
3. Write a well-defined and detailed prompt that describes your web application. This prompt will serve as the blueprint for your application. Mention the parameters for functionality, interface, and back end so the first output is detailed enough and you can easily iterate on it.
4. Enter your prompt in the Bind AI code generator and ask it to create an extensive HTML file with CSS and JavaScript embedded in it. ↑
5. Put your generated code into the IDE and hit the ‘Run’ button. ↑
6. Click on the ‘Preview’ button, and your application will be on your screen. ↑
7. Iterate from there and ask the code generator for improvements.
8. Test your app with real users to gather feedback and ensure smooth interaction.
Real-World Example: Let’s create OmniBot, a ChatGPT alternative using Bind AI
Here’s video demo showing OmniBot in action: https://player.vimeo.com/video/1036698986?badge=0&autopause=0&player_id=0&app_id=58479
The image above shows an AI-powered chatbot called ‘OmniBot,’ coded and deployed using Bind AI. It can do anything you want – writing, arithmetic, coding, etc., and has cache memory for chats. Now, we’ll walk you through how it was created to show how you can do it too.
Step 1: Write and Enter the Prompt
As you can see, our initial prompt has clear requirements. It asks the code generator to create something functional and details ‘how’ that thing will function (in this case, OpenAI API key) and is clear about the structure and design of the application. That gives you a good start. This is what the first output looked like:
Not too bad, is it?
Step 2: Iteration and Improvements:
Now, this is where things start to get more complex and need more keen eyes. You have generated what you needed, but it won’t exactly be what you wanted. So iteration is the key here. For OmniBot, we asked Bind AI to make various changes to the design layout and back end, as you can see here:
NOTE: For each iteration and revision you make, re-run the code and preview. Bind AI Copilot will generate a new link each time.
More.
And more.
And more.
To get this, a functional chatbot that people can use:
Now, this looks much better. But for this example, there’s one more important part, and that is:
Step 3: Adding the API Key
Your chatbot will only respond with errors to your messages unless you use a working API key. So, make sure you have a working API key, and replace it with ‘your-openai-api-key-here’; and it’ll work perfectly.
As for how to get your OpenAI API key, follow these steps:
- Visit the OpenAI Platform: Go to platform.openai.com and sign in with your OpenAI account. If you do not have an account, you will need to create one.
- Access Your Profile: Once logged in, click on your profile icon located at the top-right corner of the page.
- View API Keys: From the dropdown menu, select the “View API keys” option.
- Create a New Key: On the API keys page, look for a button labeled “Create New Secret Key.” Click this button to generate a new API key.
- Copy Your API Key: After creating the key, make sure to copy it immediately. The key will only be displayed once, so if you navigate away without copying it, you will not be able to retrieve it again.
Step 4: Deployment and Hosting
With your application ready, it’s time to make it accessible by deploying it:
- Upload to a Repository: Store your code on platforms like GitHub (which is also supported by Bind AI as an integration), GitLab, or Bitbucket for version control. Create a repository, add your files, commit, and push your code.
- Select a Hosting Service: Use hosting platforms like Netlify, Vercel, or Heroku. These services are user-friendly and offer free tiers for small projects.
- Deploy Your App:
- Netlify/Vercel: Connect your GitHub repo for automatic builds and deployment.
- Heroku: Use their CLI tools to push your code directly from the command line.
- Test and Share: Verify that the hosted app works smoothly, then share the live link for feedback or usage.
Your application is now live and ready for users!
FAQ
1. What is Bind AI, and how does it help in creating web applications?
Bind AI is an AI-powered platform that allows users to generate and deploy web applications through basic NL prompts. It simplifies the web development process by using advanced models like Claude 3.5 Sonnet, GPT-4o, Llama, and Codestral, among many others, to create code and build functional applications, such as chatbots or AI image generators.
2. Do I need to be a coding expert to use AI for building web applications?
You do not need to be an ‘expert’ per se, but you do need basic knowledge of GitHub and how to push code to a server to publish applications. You can further iterate and customize the code without needing in-depth programming knowledge, making web development more accessible.
3. What are the steps to create an AI-powered web application?
The general steps include: selecting a model on Bind AI, defining the type of application you want to build, writing a detailed prompt, generating the code (HTML, CSS, JavaScript), testing the app, iterating based on feedback, and finally, deploying your app for real user interactions.
4. Can I make complex applications with AI, like a chatbot or an AI image generator?
Yes, AI can be used to create complex applications such as chatbots or AI image generators. You can generate code for such applications by specifying detailed functionality and design requirements in your prompt. The AI models can handle sophisticated tasks like integrating APIs, creating memory features, and more.
5. Is Bind AI free to use? What are the available plans and pricing?
Yes, Bind AI has a free-to-use model. For more advanced features like Claude 3.5 Sonnet, GitHub integration, and more, you can consider the Premium plan starting at $18/month, or the Scale plan which gives you up to 5 million monthly tokens at $39/month, charged annually. You can learn more about Bind AI pricing here.
The Bottom Line
AI has made coding and deploying your web applications immensely easy. With Bind AI in particular, you get various benefits, such as advanced models like Claude 3.5 Sonnet, which made the abovementioned use case possible and features to edit your generated code in the built-in IDE and test it in real-time. By following a structured approach—defining objectives, selecting appropriate output languages, collecting data, and building intuitive interfaces—you can successfully develop functional AI-powered web applications.
Get started here.