Automate RAG System with Source Citations Using Qdrant, Google Gemini, and OpenAI

This workflow is designed to streamline the process of document retrieval and AI response generation. It begins by creating a collection in Qdrant to store vectorized documents. Documents from a specified Google Drive folder are downloaded, split into manageable chunks, and embedded using OpenAI's embedding service. These embeddings, along with metadata, are stored in the Qdrant collection. When a user submits a query, the workflow retrieves the most relevant document chunks and uses Google Gemini to generate a response. The final output includes the AI-generated response and a list of cited source documents, ensuring transparency and traceability.