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Retrieval-augmented generation, or RAG, introduces some serious capabilities to your large language models (LLMs). These applications can answer questions about your specific corpus of knowledge, while leveraging all the nuance and sophistication of a traditional LLM. This tutorial will take you through the ins and outs of creating a Q&A chatbot using RAG. The application will: Retrieve data from a MongoDB Atlas database. Embed and store documents as vector embeddings.