mfester

Interesting. Could you share more about the performance characteristics of EdgeDB + TypeScript vs say Prisma + other DB?

Embeddings are created using OpenAI's ada model. They are stored in Supabase with the vector extension, which offers a simple way to compute vector similarities. Then the associated sections are added to the prompt context.

Thanks!

Yes, we plan to do this in background workers soon so that it can carry the load.

The way it went is: we built this as part of Motif for the past month, and our users loved it. Many asked for a way to add this feature to their existing sites, so we made a standalone platform that streamlines the process, and open sourced it :)

Yes, this will come, we had to start somewhere. Would love a PR on this, should be straightforward.

Handmade, but indeed Tailwind.

Haven't made a comparison yet but would love to hear about any findings. So far, for the intended use cases, meaning narrative docs with lots of text, images and code, it works really well. We're still breaking up the Markdown into sections and comparing embeddings as this strikes a good balance between performance and cost, but will also plan to let users experiment with other approaches, such as sending entire corpuses of text to GPT-4.