Welcome to the ultimate starter repository for building state-of-the-art web applications powered by large language models (LLMs). This guide will walk you through setting up Create T3 Turbo AI, a powerhouse that combines several technologies like Turborepo, tRPC, Prisma, Next.js, OpenAI, and Langchain.

Folder Structure

The folder structure is organized in a way that promotes ease of use and maintainability:

• .github – Contains workflow settings for CI with pnpm cache.
• .vscode – Recommendations for VSCode extensions and settings.
• apps – Next.js and React components, including Tailwind CSS and typesafe API server.
• packages – Components for API routing, authentication, and database access.

Quick Start

Ready to dive in? Here’s how to get your application up and running!

1. Setup Dependencies

Start by installing the necessary dependencies.

pnpm i

2. Update Database Provider

Navigate to packages/db/schema.prisma and change your database provider:

provider = postgresql
provider = sqlite

3. Configure Environment Variables

Make sure to add the environment variables your application needs. Use the provided .env.example as a template:

cp .env.example .env

Don’t forget to include your OPENAI_API_KEY!

4. Push the Prisma Schema

After configuration, push the schema to your database:

pnpm db:push

Deployment Steps

Once you’re set up, it’s time to deploy your application!

Deploy to Vercel

Deploying to Vercel is straightforward:

1. Create a new project on Vercel and select apps/nextjs as the root directory.
2. Configure your build settings by following the official Turborepo guide.
3. Add your DATABASE_URL environment variable.
4. And voila! Your application is now deployed!

Troubleshooting

If you encounter any issues during installation or deployment, consider the following troubleshooting steps:

• Ensure your Node.js and pnpm versions are compatible with the dependencies.
• Double-check your database configurations and connectivity.
• Refer to the error logs in your Vercel project for more specific guidance.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Future Enhancements

The project is continuously evolving! Here are some upcoming features:

• Organizing prompts in a prompt library.
• Adding support for PromptLayer examples.
• Implementing Vercel Edge Functions for optimized performance.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.