Build a Fully Local RAG System with rlama and Ollama—No Cloud, No Dependencies

Rlama is a tool for building local, offline Retrieval-Augmented Generation (RAG) systems without cloud services or dependencies. It streamlines document ingestion, embedding generation, and storage in a hybrid vector store. Rlama supports both large and small language models, with a focus on optimizing smaller models. The tool offers enhanced document management, hybrid searches, and improved retrieval accuracy through recent updates to its hybrid store and document metadata handling.