Chunking : Strategies, Considerations and Optimization (Part 2 of RAG Series)

Bits, pieces and coherency

Chandan Durgia
An Idea (by Ingenious Piece)

--

Photo by Markus Spiske on Unsplash

This is part 2 of the “Retrieval-Augmented Generation (RAG) — Basics to Advanced Series”. Links to other blogs in the series are at the bottom of this blog. Taking forward from part 1, in this blog we will focus on the “Chunking” component which is relevant for chunking of source content and chunking of query. (highlighted in Blue). Since, fundamentally the concept is similar, we will cover this together.

Image by Author: RAG Architecture

Chunking Basics

As discussed earlier, the data from the source document (for retrieving information) or query has to be converted into a mathematical form. The first step in this process is breaking down the text into smaller chunks of text. Hereafter called “Chunking”. The idea is once the text is chunked appropriately, every chunked part would be converted into a mathematical form (Embedding — next blog in the series).

Sounds straightforward right, but here comes some challenges — how to go about chunking — should we chunk it by every word, every few words, every sentence, few sentences together etc.? What would…

--

--

No responses yet