AI & Vectors
The best vector database is the database you already have.
Supabase provides 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.
The toolkit includes:
- A vector store and embeddings support using Postgres and pgvector.
- A Python client for managing unstructured embeddings.
- An embedding generation process using open source models directly in Edge Functions.
- Database migrations for managing structured embeddings.
- Integrations with all popular AI providers, such as OpenAI, Hugging Face, LangChain, and more.
Check out all of the AI templates and examples in our GitHub repository.
Headless Vector Search
Berri AI Boosts Productivity by Migrating from AWS RDS to Supabase with pgvector
Mendable switches from Pinecone to Supabase for PostgreSQL vector embeddings