Are you new to local AI workflows? Looking to better understand LLMs and Retrieval-Augmented Generation (RAG)? Don’t want to spend a fortune on a hosted solution?
In this tutorial, we will learn how to use Lima to create a repeatable local Linux environment geared towards working with local LLMs and RAG. We will use Ollama to run a local language model, add a small set of local documents, generate embeddings, store them in a local vector database, and then use retrieval-augmented generation to answer questions from that document set. It is designed for beginners who want to get hands-on with local LLM development.
Attendees will leave with a configured lab, reusable examples, and a clearer understanding of how to build, test, and expand local RAG workflows.
Alex is an open-source enthusiast with over 25 years of experience in Linux, Kubernetes, and other open-source projects. He specializes in helping people navigate complex technical challenges and is passionate about making systems and concepts more accessible and understandable. He is a frequent presenter and volunteers to mentor aspiring technologists. A lifelong learner, he believes the ability to learn is the most valuable skill in tech and is dedicated to helping others grow through shared knowledge.