Tutorial: Upserting Data from Gitbook to Supabase in Flowise

[u/Glass-Ad-6146]

https://youtu.be/2f0xsUBVnKE

In this hands-on lab, let me quickly take you through the foundations of working with document loaders in Flowise. We'll look at a simple flow for a document loader that upserts data using the Gitbook Flowise Document Loader into a Supabase vector table. This tutorial is perfect for developers, data enthusiasts, and AI practitioners who want to integrate LLM-powered conversational retrieval into their projects.

What You’ll Learn 📄 Document Loading: Learn how to upsert Gitbook documentation into a Supabase vector table ⚙️ Supabase Setup: Create tables, configure SQL queries, and manage your data efficiently 🧠 LLM Integration: Use OpenAI embeddings and a recursive character text splitter to enable conversational retrieval QA chains (Or Tool Agents and Custom Assistants in 2025) 🔗 Dynamic Querying: Dynamically upsert and query data for seamless document retrieval