AI Inference in Supabase Edge Functions

Since Supabase Edge Runtime v1.36.0 you can run the gte-small model natively within Supabase Edge Functions without any external dependencies! This allows you to easily generate text embeddings without calling any external APIs!

Semantic Search with pgvector and Supabase Edge Functions

This demo consists of three parts:

1. A generate-embedding database webhook edge function which generates embeddings when a content row is added (or updated) in the public.embeddings table.
2. A query_embeddings Postgres function which allows us to perform similarity search from an egde function via Remote Procedure Call (RPC).
3. A search edge function which generates the embedding for the search term, performs the similarity search via RPC function call, and returns the result.

Deploy

• Link your project: supabase link
• Deploy Edge Functions: supabase functions deploy
• Update project config to enable webhooks: supabase config push
• Navigate to the database-webhook migration file and insert your generate-embedding function details.
• Push up the database schema supabase db push

Run

Run a search via curl POST request:

curl -i --location --request POST 'https://<PROJECT-REF>.supabase.co/functions/v1/search' \
    --header 'Authorization: Bearer <SUPABASE_ANON_KEY>' \
    --header 'Content-Type: application/json' \
    --data '{"search":"vehicles"}'