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How to Integrate Retrieval-Augmented Generation (RAG) in Your LLM Applications
Retrieval-Augmented Generation (RAG) is a powerful technique that enhances large language models (LLMs) by combining their generative capabilities with the ability to retrieve relevant external information. Outline 1. Introduction * Importance and benefits of RAG 2. Understanding Retrieval-Augmented Generation * What is RAG? * Key differences from traditional LLMs 3. Steps to Integrate