Building a RAG pipeline without OpenAI

RAG stands for Retrieval Augmented Generation. The idea is simple: before your model answers a question, it first searches a database of relevant knowledge and uses that information to answer better. I built this entirely without OpenAI — my own embedding model, my own vector database, my own retrieval logic. Why RAG matters Without RAG, your model answers purely from what it learned during training. It might hallucinate, it might be outdated, it can't cite sources. With RAG: Question comes in S