Supabase RAG Chatbot with Persistent Chat Memory

This retrieval-augmented generation workflow builds a chatbot that answers questions using your own documents stored in a Supabase vector database. The AI agent is instructed to always consult the Supabase knowledge tool before answering, ensuring responses stay grounded in your actual content rather than generic model knowledge, while Postgres-backed memory keeps track of the ongoing conversation. It's a solid starting template for businesses, support teams, or internal tools that need an accurate, document-aware chatbot without building the RAG pipeline and memory handling from scratch.

Category: RAG & Knowledge Base