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This chapter provides a comprehensive guide to designing and building Retrieval-Augmented Generation systems using LangChain. We will explore each stage of the RAG pipeline from loading and preprocessing data, chunking and embedding, indexing into vector stores, to retrieval and final response generation. Practical techniques for improving retrieval quality and ensuring ethical, explainable behavior are also covered.

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Building Retrieval-Augmented Generation (RAG) Systems

  • 章节

  • 发表日期：

    2025年

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  • Sanath Raj B Narayan,
  • Nitin Agarwal

摘要

This chapter provides a comprehensive guide to designing and building Retrieval-Augmented Generation systems using LangChain. We will explore each stage of the RAG pipeline from loading and preprocessing data, chunking and embedding, indexing into vector stores, to retrieval and final response generation. Practical techniques for improving retrieval quality and ensuring ethical, explainable behavior are also covered.