Interactive Supabase RAG Chatbot for Knowledge Base

This n8n workflow builds an interactive knowledge base chatbot leveraging Retrieval-Augmented Generation (RAG) with Supabase. It ingests files from Google Drive (PDFs, DOCX, TXT, XLSX, CSV, Sheets), extracts content, generates embeddings, and stores in Supabase for vector search, enabling accurate AI responses via chat.

Key benefits include automating file ingestion to eliminate manual work, handling duplicates and errors for data integrity, supporting text and tabular data, and integrating seamlessly with chat interfaces. It saves hours on knowledge management and powers context-aware queries.

Ideal for Health & Fitness pros building info bases from research papers/spreadsheets, knowledge managers centralizing docs, data teams processing files, and developers creating RAG apps. Triggers on file changes, processes intelligently, prepares for real-time chat retrieval.

Workflow flow: Detects files, validates/processes, checks duplicates, extracts/embeds content, stores in Supabase tables for RAG querying in chatbots.