A comprehensive guide to implementing retrieval-augmented generation (RAG) applications using Ruby. Covers the complete pipeline from data preparation and embedding generation to retrieval setup with Meilisearch and LLM integration. Includes practical code examples for building a lightweight RAG system without heavy frameworks, demonstrating how to load documents, generate embeddings via OpenAI API, implement fast retrieval with Meilisearch, and create a CLI interface. Compares Ruby's approach to Python's ecosystem and highlights Ruby's strengths in simplicity and direct integrations for smaller-scale RAG applications.
Table of contents
What is a RAG application in Ruby?Why use RAG with Ruby?What tools are needed for RAG in Ruby?Step-by-step guide to building a RAG app in RubyHow is RAG in Ruby different from Python?Unlocking the power of RAG with RubySort: