Internal linking.

apps/docs/pages/guides/database/extensions/pgvector.mdx

@@ -7,7 +7,7 @@ export const meta = {
     'pgvector: a PostgreSQL extension for storing embeddings and performing vector similarity search.',
 }
 
-[pgvector](https://github.com/pgvector/pgvector/) is a PostgreSQL extension for vector similarity search. It can also be used for storing [embeddings](https://en.wikipedia.org/wiki/Word_embedding).
+[pgvector](https://github.com/pgvector/pgvector/) is a PostgreSQL extension for vector similarity search. It can also be used for storing [embeddings](https://supabase.com/blog/openai-embeddings-postgres-vector).
 
 ## Concepts
 
@@ -91,9 +91,12 @@ const { data, error } = await supabase.from('posts').insert({
 })
 ```
 
-## Resources
+## More pgvector and Supabase resources
 
-- Source code: [github.com/pgvector/pgvector](https://github.com/pgvector/pgvector/)
+- [Supabase Clippy: ChatGPT for Supabase Docs](https://supabase.com/blog/chatgpt-supabase-docs)
+- [Storing OpenAI embeddings in Postgres with pgvector](https://supabase.com/blog/openai-embeddings-postgres-vector)
+- [A ChatGPT Plugins Template built with Supabase Edge Runtime](https://supabase.com/blog/building-chatgpt-plugins-template)
+- [Template for building your own custom ChatGPT style doc search](https://github.com/supabase-community/nextjs-openai-doc-search)
 
 export const Page = ({ children }) => <Layout meta={meta} children={children} />