From 605d36ca5cdf0dfeb04a46caab75507a0d7f9af3 Mon Sep 17 00:00:00 2001 From: Copple <10214025+kiwicopple@users.noreply.github.com> Date: Thu, 1 Jun 2023 10:32:51 -0600 Subject: [PATCH] Updates based on Ant's suggestions --- apps/www/data/products/vector/pageData.tsx | 8 ++++---- apps/www/pages/vector/Vector.tsx | 4 ++-- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/apps/www/data/products/vector/pageData.tsx b/apps/www/data/products/vector/pageData.tsx index c9b360178e8..b4cea2e68a1 100644 --- a/apps/www/data/products/vector/pageData.tsx +++ b/apps/www/data/products/vector/pageData.tsx @@ -12,15 +12,15 @@ export default { title: 'Supabase Vector', h1: ( - The best vector database
- is the database you already have + The open source Vector Toolkit
+ for Postgres
), subheader: ( <> - An open source toolkit for developing AI applications using Postgres and pgvector. -
Use the Supabase client libraries to store, index, and query your vector embeddings at scale. +
+ Build AI applications with Postgres and pgvector: the best vector database is the database you already have. ), image: '/images/product/vector/vector-hero.svg', diff --git a/apps/www/pages/vector/Vector.tsx b/apps/www/pages/vector/Vector.tsx index 398ca5cf381..68c2b0e25a9 100644 --- a/apps/www/pages/vector/Vector.tsx +++ b/apps/www/pages/vector/Vector.tsx @@ -21,9 +21,9 @@ const EnterpriseCta = dynamic(() => import('~/components/Sections/EnterpriseCta' function VectorPage() { // base path for images const { basePath } = useRouter() - const meta_title = 'Supabase Vector | The best vector database is the database you already have.' + const meta_title = 'Supabase Vector | The open source Vector Toolkit for Postgres.' const meta_description = - 'An open source toolkit for developing AI applications using Postgres and pgvector. Integrate Supabase Vector database with your favorite ML-models to store, index and access vector embeddings for any AI use case.' + 'An open source toolkit for developing AI applications using Postgres and pgvector. Use the Supabase Vector Toolkit with your favorite ML-models to store, index, and access vector embeddings for any AI use case.' return ( <>