Automate RAG Document Updates with Qdrant and OpenAI Integration

This n8n workflow provides a robust solution for managing and updating documents within a Retrieval Augmented Generation (RAG) system. By integrating with OpenAI's powerful embedding models and Qdrant's scalable vector database, you can ensure your RAG knowledge base remains current and accurate. The workflow handles the creation of Qdrant collections, generation of embeddings for new or updated documents, and efficient insertion into the vector store. It also includes functionality to delete outdated documents based on file IDs, simplifying data lifecycle management. Ideal for developers and data engineers looking to build and maintain sophisticated RAG applications.