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 (
<>