This workflow connects Supabase Storage with an AI-powered chatbot to let users query and interact with their stored documents. It automates file ingestion, processing, and embedding, making it easy to retrieve context-aware answers from PDFs and text files stored in Supabase.
The setup avoids duplicate processing, extracts content from files, creates vector embeddings via OpenAI, and stores them in a Supabase vector store. Finally, it integrates an AI Agent that responds to chat queries using the processed document knowledge base.
Key Features:
- 🔄 Automated File Sync – Fetches files from Supabase Storage and checks against database records to avoid reprocessing.
- 📂 File Handling – Supports PDF and text files with type-specific extraction.
- ✂️ Content Chunking – Splits large documents into smaller text chunks for accurate AI responses.
- 🤖 AI Embeddings – Uses OpenAI embeddings to vectorize document content.
- 🗄️ Supabase Vector Store Integration – Stores embeddings with metadata for efficient search and retrieval.
- 💬 Chatbot Interaction – Enables natural-language queries against stored files via an AI Agent.
- ⚡ Scalable & Extensible – Can be customized to support additional file types, storage buckets, or AI models.
