Chunking Strategy for LLM Application: Everything You Need t

Chunking strategy is a method used in large language model (LLM) applications to break down long or complex text into smaller, manageable parts called “chunks.” This helps the LLM process information more effectively without missing important details or context. Since many LLMs have token or character limits, chunking ensures that your input fits within those limits while still delivering accurate and relevant results.