Generative AI with Python

6.6    Summary

In this chapter, we delved into the concept of RAG. This powerful tool can greatly assist you when you need to enhance an LLM response with your own content or documents. In most cases, this approach is more promising and preferred to fine-tuning a complete LLM.

We started with understanding the implementation of naïve (or standard) RAG, which consists of the retrieval, augmentation, and generation process. Later, we studied more detailed techniques to improve the system at different stages, including improvement strategies for pre-retrieval, in which the indexing pipeline is adapted in different ways.

In advanced retrieval techniques, you learned how a hybrid RAG system functions. Other techniques like query expansion and context ...