What is RAG Chunks?
It is a version of long documents divided into small pieces so that artificial intelligence can understand them more easily.
Overview
The amount of information AI models can read at once is limited. RAG Chunks divides large documents into meaningful and small chunks, allowing artificial intelligence to find exactly the information it needs. In this way, the model gives correct answers by focusing only on the relevant page instead of reading a huge book.
How it works
When documents are uploaded to the system, they are automatically divided into small pieces and each piece is numbered. When you ask a question, the system finds the most relevant piece and presents it to the artificial intelligence.
Where it is used
It is used in the data preparation phase, which forms the basis of RAG systems.
Commonly confused with
It is important not only to divide the data, but to divide it while preserving meaningful integrity.
Frequently asked questions
What happens if the pieces are too small?
AI may lose context, so the size of the fragments should be balanced.
Why don't we give the full text?
Not only does the cost increase, but the model may get lost in too much information and give the wrong answer.
Related terms
Related tools
This explanation was written in plain language for TreScout and machine-translated from the Turkish original · the Turkish version prevails. If something looks wrong or missing, write to hello@trescout.com. Read in Turkish →