Automated Document Management and Q&A with Qdrant and Google Drive

This n8n workflow enables efficient management and updating of documents within a Retrieval-Augmented Generation (RAG) system. The process begins with manual or automated triggers, such as a test button or chat message, and involves multiple steps to upload, index, and update documents into a Qdrant vector store, leveraging OpenAI embeddings for semantic understanding. The workflow integrates Google Drive for sourcing documents, employs text splitters for chunking content, and utilizes advanced language models like Google Gemini for question answering capabilities. It supports full or incremental updates, ensuring the vector database remains current, and is suitable for deploying intelligent chatbots or knowledge management systems that require dynamic document indexing and retrieval.