TLBrowse is a fascinating project that showcases the potential of just-in-time software, where web pages are dynamically generated based on user interactions, rather than being pre-rendered. This approach, enabled by large language models, represents a significant shift in how we think about software delivery.

The core functionality of TLBrowse is an "infinite web canvas" where users can navigate and interact with AI-generated web pages. By simply typing a URL, the application dynamically creates a web page on the fly, allowing users to explore and interact with the content. This dynamic generation extends to deeper levels, where users can click into specific sections of the page, and the application generates new pages accordingly.

The implications of this technology are profound. Instead of maintaining a codebase and deploying updates, software can be generated in the moment, tailored to the user's specific needs and context. This "just-in-time" approach has the potential to revolutionize software development, reducing the overhead of traditional software delivery and enabling more personalized and adaptive experiences.

To get started with TLBrowse, you'll need to set up an Anthropic account and a Clerk account for authentication. The installation process is straightforward, and the project's GitHub repository provides detailed instructions. Once set up, you can explore the infinite web canvas, experiment with different URLs, and even download and edit the generated code.

As you delve into TLBrowse, consider the broader implications of just-in-time software. How might this technology transform the way we build and interact with web applications? What new possibilities does it open up for personalization, adaptability, and rapid innovation? Share your thoughts and ideas in the comments below, as we continue to explore the future of software development.

TL;DR: TL Browse is a new project that allows you to dynamically create web pages using AI-generated content. It leverages large language models to generate the content and layout of web pages on-the-fly, based on the user's input. This project showcases the potential of "just-in-time software" where applications are built and delivered in the moment, rather than being pre-rendered.

The key features of TL Browse include:

• Infinite web canvas where you can navigate and explore AI-generated web pages
• Ability to generate web pages by simply typing a URL (e.g. "bestbuy.com")
• Dynamically generated pages that can be further edited and customized
• Support for various AI models, including OpenAI, Anthropic, and others
• Local deployment option to run the AI models directly on your machine

To get started with TL Browse, you'll need to set up an Anthropic account and a Clerk account for authentication. The installation process is a bit involved, but the project's GitHub repository provides detailed instructions. Once set up, you can start exploring the infinite web canvas and generating dynamic web pages to your heart's content.

This project is a fascinating glimpse into the future of software development, where AI-powered "just-in-time" applications could revolutionize the way we create and interact with digital experiences.

The TL Browse project allows you to not only generate web pages on the fly, but also customize and download the generated content. Here's how you can work with the AI-generated web pages:

1. Customization: Once a web page is generated, you can easily edit the content by clicking on the various elements. The project provides a set of editing tools that allow you to modify the text, images, and other components of the page.

2. Downloading the Code: If you're satisfied with the generated page, you can download the code by clicking the "Download" button. This will provide you with the HTML, CSS, and JavaScript files that make up the web page, which you can then further customize or deploy as needed.

3. Refreshing the Page: If you want to generate a new version of the web page, you can simply click the "Refresh" button. This will create a fresh instance of the page based on the current URL or input.

4. Saving and Sharing: The project also allows you to save the current state of the canvas, including all the generated pages. You can then share the unique URL with others, who can then explore and interact with the same set of AI-generated web pages.

By leveraging the power of large language models, the TL Browse project demonstrates the potential of "just-in-time" software generation, where web pages are created on-the-fly based on user input and context. This approach opens up new possibilities for rapid prototyping, content generation, and personalized web experiences.

To get started with TLBrowse, you'll need to set up your Anthropic and Clerk accounts. Here's how:

1. Create an Anthropic Account:

   • Go to the Anthropic website console at console.anthropic.com.
   • Click on "Create key" to generate your Anthropic API key.
   • Copy the generated API key.

2. Create a Clerk Account:

   • Sign up for a Clerk account at clerk.com.
   • Create a new app in Clerk.
   • Copy the Clerk publishable key and secret key.

3. Configure the Environment Variables:

   • In Visual Studio Code, navigate to the TLBrowse project folder.
   • Create a new file named .env.local in the project root.
   • In the .env.local file, add the following lines:

     ANTHROPIC_API_KEY="your_anthropic_api_key"
     CLERK_PUBLISHABLE_KEY="your_clerk_publishable_key"
     CLERK_SECRET_KEY="your_clerk_secret_key"
     

   • Replace your_anthropic_api_key, your_clerk_publishable_key, and your_clerk_secret_key with the respective values you copied earlier.
   • Save the .env.local file.

4. Update the Layout.tsx File:

   • In the TLBrowse project, open the layout.tsx file.
   • Find the ClerkProvider component and add the publishableKey prop, passing in the Clerk publishable key:

     <ClerkProvider publishableKey="your_clerk_publishable_key">
       {/* Rest of the code */}
     </ClerkProvider>
     

   • Save the layout.tsx file.

Now that you have your Anthropic and Clerk accounts set up, you can proceed to run the TLBrowse project locally.

To use a local or custom AI model with TLBrowse, follow these steps:

1. In the route.ts file, replace the cloudModel value with the model you want to use, such as 'gpt-4'.

2. In the same route.ts file, replace the process.env.CLOUD_KEY value with your OpenAI API key.

3. In the m.ts file, add your OpenAI API key to the process.env.OPENAI_API_KEY value.

4. In the client.ts file, replace the OPENAI_URL value with the URL of your local model.

After making these changes, the TLBrowse application should now use your local or custom AI model instead of the default Anthropic model. Keep in mind that you may need to adjust the code further depending on the specific requirements of your chosen model.