+
diff --git a/apps/www/data/products/vector/pageData.tsx b/apps/www/data/products/vector/pageData.tsx
index 93938b32948..4049aafadce 100644
--- a/apps/www/data/products/vector/pageData.tsx
+++ b/apps/www/data/products/vector/pageData.tsx
@@ -5,29 +5,29 @@ import PGvectorImg from '~/components/Products/VectorAI/PGvectorImg'
import DeployGlobally from '~/components/Products/VectorAI/DeployGlobally'
import IntegrationsImage from '~/components/Products/VectorAI/IntegrationsImage'
-export default {
+export default (isMobile?: boolean) => ({
metaTitle: '',
metaDescription: '',
heroSection: {
announcement: {
url: 'https://www.ai.engineer/summit/schedule/supabase-vector',
- badge: 'AI Engineer Summit',
- announcement: 'Join us in San Francisco, Oct 8–10',
+ badge: 'Happening now',
+ announcement: 'AI Engineer Summit',
target: '_blank',
+ hasArrow: !isMobile,
},
title: 'Supabase Vector',
h1: (
- The Postgres Vector database
+ The Postgres Vector database
and AI Toolkit
),
subheader: (
<>
An open source Vector database for developing AI applications.
-
- Use pgvector to store, index, and access embeddings, and our AI toolkit to build AI
- applications with Hugging Face and OpenAI.
+
Use pgvector to store, index, and access embeddings, and
+ our AI toolkit to build AI applications with Hugging Face and OpenAI.
>
),
image: '/images/product/vector/vector-hero.svg',
@@ -337,4 +337,4 @@ docs.query(
},
],
},
-}
+})
diff --git a/apps/www/pages/vector/Vector.tsx b/apps/www/pages/vector/Vector.tsx
index 53aea537162..94fd4c07f8c 100644
--- a/apps/www/pages/vector/Vector.tsx
+++ b/apps/www/pages/vector/Vector.tsx
@@ -3,8 +3,9 @@ import dynamic from 'next/dynamic'
import { useRouter } from 'next/router'
import DefaultLayout from '~/components/Layouts/Default'
+import { useBreakpoint } from 'common'
import { PRODUCT_SHORTNAMES } from '~/lib/constants'
-import pageData from '~/data/products/vector/pageData'
+import vectorPageData from '~/data/products/vector/pageData'
import 'swiper/swiper.min.css'
@@ -20,10 +21,12 @@ const EnterpriseCta = dynamic(() => import('~/components/Sections/EnterpriseCta'
function VectorPage() {
// base path for images
+ const isXs = useBreakpoint(640)
const { basePath } = useRouter()
const meta_title = 'Supabase Vector | The Postgres Vector database.'
const meta_description =
'An open source Vector database for developing AI applications. Use pgvector to store, index, and access embeddings, and our AI toolkit to build AI applications with Hugging Face and OpenAI.'
+ const pageData = vectorPageData(isXs)
return (
<>