Automate Course Outline to Vector Database with Google Drive and Pinecone

The "Bundle RAG Upload" workflow is designed to seamlessly integrate your course module outlines into a powerful vector database. It begins by monitoring a specified Google Drive folder for new or updated documents. Once detected, it retrieves the files, splits them into manageable text segments, and generates embeddings using OpenAI. These embeddings are then efficiently uploaded to a Pinecone vector store, specifically within the 'Course Outlines' namespace. This automation is a crucial step in building robust Retrieval Augmented Generation (RAG) systems for educational content, enabling sophisticated question-answering and content retrieval capabilities.