Building Advanced Q&A and Search Applications Using Retrieval-Augmented Generation (RAG)

In this chapter, you will learn about Retrieval-Augmented Generation (RAG), an innovative approach that combines retrieval-based methods with large language models (LLMs) to improve the accuracy and relevance of generated responses. By the end of this chapter, you will understand the fundamental concepts of RAG, how it integrates with LLMs, and how to implement RAG using LangChain, Pinecone, and OpenAI. You will explore various strategies to enhance the RAG process for specific use cases. You will gain practical skills building advanced question-answering and information retrieval systems Using Retrieval-Augmented Generation (RAG).