laf VS supabase

LAF (https://github.com/labring/laf) now supports ChatGPT AI generation function, providing a seamless and efficient way for developers to deploy and scale AI applications on Alibaba Cloud Function Compute. With this new feature, developers can easily leverage the power of ChatGPT to generate high-quality text content and integrate it with their own applications.

Using LAF and ChatGPT, developers can quickly build and deploy AI applications, such as chatbots, recommendation systems, and content generators, without having to worry about infrastructure or scaling issues. With the automatic scaling capabilities of Function Compute, developers can focus on building the AI models and let LAF take care of the deployment and scaling aspects.

In addition, LAF provides a secure and reliable environment for AI application development, with features such as access control, logging, and exception handling. This ensures that your AI applications are always available and performing at their best.

Overall, the support of ChatGPT in LAF brings a new level of efficiency and scalability to AI application development, making it easier than ever before to build and deploy high-quality AI applications

So open source is a big trend, and Tencent Cloud developed open source alternatives https://github.com/labring/laf also because of this incident

I didn't really give much thought as to which backend I would use. I already had 2 projects in Supabase (BOXCUT & MineWork), but also a few projects in Firebase too. I was more concerned at the time at actually building the product.

Sign up for SupaBase: Head over to SupaBase and sign up. Create a new workspace and project with your preferred names.

Setting up Supabase Create a new Supabase project, and get the connection string for the database from settings > database.

Supabase (start for free)

Built with Supabase, Astro, Unreal Speech, Stable Diffusion, Replicate, Metropolitan Museum of Art

Supabase will be used for storing article data in the database and the cover image of the article in storage. Chakra UI will be used to provide style to the elements. By using both, we can build the blog with ease.

For AutoRepurpose, I opted for Supabase as the backbone of the backend. It has reliably supported Penelope AI, which garnered over 15k users in 2022 without any issues.

Semantic search demo

1. Create a new Supabase project: Visit Supabase and create a new project.

Supabase positions itself as the "open source Firebase alternative." It was founded in 2020 and is a developer-friendly serverless database platform that supports over 20 frameworks, including popular tools like Next.js, React, Nuxt, Svelte, Flutter, and Vue.