RAG stands for Retrieval Augmented Generation. Why do we even need RAG?? To answer this lets take a look at What LLMs and SLMs are. LLM(Large Language Model). Data on several categories(generalized) will be given as input. From that, a model would be created. What is a model ? To understand this, lets take mathematical equation of a straight line y = mx +c Lets take x values to be 1, 2, 3, ... and y values to be 2, 4, 6, 8, 10. We can use whatever values for m and c to get our desired y value(like 2, 4 etc). Instead of a simple linear equation, we can also consider double, cubic or equations(order of the variables like x^2, x^3 etc...). When we say a model is os of 4b parametrs, 120b parameters and all , it refers to a big equation. Using the input data, a mathematical equation is being created. Larger the equation, more better the result will be. i.e if model is exposed and trained on several amount of data, results generated will also be more relevant and good. LLMs predict the next word.…