I'm lucky enough to have 95% of my docs in small markdown markdown files so I'm just... not (+). I'm using SQLite FTS5 (full text search) to build a normal search index and using that. Well, I already had the index so I just wired it up to my mastra agents.
Each file has a short description field, so if a keyword search surfaces the doc they check the description and if it matches, load the whole doc.
This took about one hour to set up and works very well.
(+) At least, I don't think this counts as RAG. I'm honestly a bit hazy on the definition. But there's no vectordb anyway.
Well, that is what the acronym stands for. But every source I've ever seen quickly follows by noting it's retrieval backed by a vectordb. So we'd probably find an even split of people who would call this RAG or not.
The backing method doesn’t matter as long as it works. This is clear from good RAG survey papers, Wikipedia, and (broadly) understanding the ethos of machine learning engineers and researchers: specific implementation details are usually means to an end, not definitional boundaries.
“The equiprobability bias (EB) is a tendency to believe that every process in which randomness is involved corresponds to a fair distribution, with equal probabilities for any possible outcome. The EB is known to affect both children and adults, and to increase with probability education. Because it results in probability errors resistant to pedagogical interventions, it has been described as a deep misconception about randomness: the erroneous belief that randomness implies uniformity. In the present paper, we show that the EB is actually not the result of a conceptual error about the definition of randomness.”
You can also find an ELI5 Reddit thread on this topic where one comment summarizes it as follows:
“People are conflating the number of distinguishable outcomes with the distribution of probability directly.”
This took about one hour to set up and works very well.
(+) At least, I don't think this counts as RAG. I'm honestly a bit hazy on the definition. But there's no vectordb anyway.