Automated Knowledge Base with AI and Vector DB

This n8n workflow automates the process of ingesting, storing, and retrieving documents using AI embeddings and a vector database integrated with Supabase. It begins by downloading a file from Google Drive, processes it to extract and split text, then generates embeddings using OpenAI’s models. These embeddings are inserted or updated into a Supabase vector database, which is configured for fast similarity searches. The workflow facilitates an interactive question-answer system, where user questions trigger retrieval of relevant documents from the vector store, and an AI model generates responses based on this context. This automation is ideal for building intelligent knowledge bases, FAQ bots, or content recommendation systems that leverage AI and database capabilities seamlessly.