Understanding Text Splitting Strategies

Large Language Models (LLMs) have a 'context window' – a limit on how much text they can process at once. If you feed them a document that's too long, they simply can't handle it all.

Text splitting is the process of breaking down large documents into smaller, manageable chunks. This makes them suitable for LLMs and helps retrieval systems find more precise information.

Imagine an LLM as a very smart person with a short-term memory limit. The context window is like that limit. If you give it too much information, it might forget the beginning or get confused.

• LLMs can only process a certain number of tokens (words or sub-words).
• Going over this limit means information is truncated or ignored.
• Smaller chunks ensure all relevant information fits and is processed effectively.