Implementing Retrieval-Augmented Generation in Elixir

The article by Shapath Neupane details the initial steps taken to implement Retrieval-Augmented Generation (RAG) using Elixir. The goal is to build a system akin to PrivateGPT by understanding and experimenting with fundamental RAG concepts. Shapath deliberately avoids using LangChain or OpenAI services to dive deeper into chunking and metadata techniques. The article covers the multi-step process of RAG, detailing each phase: Document Ingestion, Chunking, Embedding, Vector Database, Retrieval & Query Processing, and Generation & Output. Shapath also shares findings and insights on the use of different embedding models and vector databases, ultimately planning to refine the system using Elixir's advanced features for background and concurrent tasks.