Building a Fully Local RAG System with Qdrant and Ollama

Some months ago I was working on a custom solution and I needed to add RAG to it. The requirements were simple but not flexible: everything had to run local, and it had to be deployable in Docker alongside the rest of the services. After looking at some options, I choose Qdrant, and after doing some experiments with it I can say it was a good decision. I know there are more complete solutions to add RAG to a local LLM setup. Frameworks like LangChain or LlamaIndex already abstract most of what I will describe here. But my requirements were not complex, and I did not want to add more dependencies and abstractions on top of a stack I already understand. Keeping things explicit made more sense for this project. This article explains what I learned. It is not a deep technical guide, it is more a conceptual explanation for developers who want to understand how Qdrant and Ollama work together before they start coding. Why Run Everything Local? My client did not want documents leaving their n