Build website Q&A chatbot with RAG, OpenAI GPT-4o-mini and Supabase Vector DB

✅ What problem does this workflow solve?

Many websites lack a smart, searchable interface. Visitors often leave due to unanswered questions. This workflow transforms any website into a Retrieval-Augmented Generation (RAG) chatbot—automatically extracting content, creating embeddings, and enabling real-time, context-aware chat on your own site.

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⚙️ What does this workflow do?

1. Accepts a website URL through a form trigger. 2. Fetches and cleans website content. 3. Parses content into smaller sections. 4. Generates vector embeddings using OpenAI (or your embedding model). 5. Stores embeddings and metadata in Supabase’s vector database. 6. When a user asks a question: - Searches Supabase for relevant chunks via similarity search. - Retrieves matching content as context. - Sends context + question to OpenAI to generate an accurate answer. 7. Returns the AI-generated response to the user in the chat interface.

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🔧 Setup Instructions

🖥️ Website Form Trigger - Use a Form / HTTP Trigger to submit website URLs for indexing.