Naive RAG vs. advanced RAG: What are the differences?

What this post added

This post details the differences between naive and advanced Retrieval-Augmented Generation (RAG) systems. It explains the workflows of both, including indexing (chunking, embedding, storing in vector databases like Meilisearch), retrieval (query embedding, similarity search), and generation. Advanced RAG is described as incorporating pre-retrieval optimization (query rewriting), multi-stage retrieval, and post-retrieval reranking/filtering. The post outlines the benefits and limitations of each approach, with naive RAG favoring simplicity and speed for prototypes and basic chatbots, while advanced RAG prioritizes accuracy and reliability for enterprise-grade applications in domains like finance and healthcare. It positions Meilisearch as a tool that can simplify the transition to advanced RAG.