RAG without preprocessing is almost useless, because unless you are careful, RAG gives you all the weaknesses of vector DBs, with all the weaknesses of LLMs! T

RAG without preprocessing is almost useless, because unless you are careful, RAG gives you all the weaknesses of vector DBs, with all the weaknesses of LLMs! The easiest example I can come up is imagine you just dump a restaurant menu into a vector DB. The menu is from a hipster restaurant and instead of having "open hours" or "business hours" the menu says "Serving deliciousness between 10:00am and 5:00pm" Naïve RAG queries are going to fail miserably on that menu. "When is the restaurant open?" "What are the business hours?" Longer context lengths are actually the solution for this problem, when context is small enough and the potential of ambiguity is high enough, LLMs are the better tool.