Intelligent Knowledge Base from Your Documents

This n8n workflow empowers you to build a dynamic and intelligent knowledge base directly from your documents. It seamlessly integrates with Google Drive to fetch your content, processes it using advanced text splitting and embedding techniques, and stores it in a vector database (Supabase with pgvector). This allows for rapid and accurate retrieval of information, enabling sophisticated question-answering capabilities. Whether you need to train an AI on your company's internal documentation, create a Q&A system for your books, or build a search engine for your research papers, this workflow provides the foundation.

The process involves downloading files from Google Drive, loading them as binary data, and then intelligently splitting the text into manageable chunks. These chunks are then embedded using OpenAI's powerful embedding models. For querying, the workflow sets up a Supabase vector store with a custom retrieval function and an OpenAI Chat Model to generate natural language answers based on the retrieved context.