diff --git a/apps/docs/pages/guides/ai.mdx b/apps/docs/pages/guides/ai.mdx index 9bec896287f..fbcd02ec4ee 100644 --- a/apps/docs/pages/guides/ai.mdx +++ b/apps/docs/pages/guides/ai.mdx @@ -4,20 +4,51 @@ export const meta = { id: 'ai', title: 'AI & Vectors', description: 'Use Supabase to store and search embedding vectors.', + subtitle: 'Use Supabase to store and search embedding vectors.', sidebar_label: 'Overview', - video: 'https://www.youtube.com/v/J9mTPY8rIXE', } -Supabase AI & Vectors makes it simple to store and search embeding vectors. +Supabase provides a number of tools to get started with Vectors and Embeddings. These tools include: -## TBD +- An embedding store using the popular [pgvector](https://github.com/pgvector/pgvector/) +- A Python Library for managing collections called [Vecs](https://supabase.github.io/vecs) -TBD +## Examples -## See also +Check out all of the AI [templates and examples](https://github.com/supabase/supabase/tree/master/examples/ai) in our GitHub repository. -- TBD +
+ {examples.map((x) => ( +
+ + + + {x.description} + + + +
+ ))} +
-export const Page = ({ children }) => +export const examples = [ + { + name: 'With supabase-js', + description: 'Use the Supabase client inside your Edge Function.', + href: '/guides/functions/auth', + }, + { + name: 'Type-Safe SQL with Kysely', + description: 'Combining Kysely with Deno Postgres', + href: '/guides/functions/kysely-postgres', + }, + { + name: 'With CORS headers', + description: 'Send CORS headers for invoking from the browser.', + href: '/guides/functions/cors', + }, +] + +export const Page = ({ children }) => export default Page