One post tagged with "chunking"

Document chunking is crucial for optimizing Retrieval-Augmented Generation (RAG) systems by breaking large documents into smaller, manageable pieces, which significantly speeds up retrieval and enhances the relevance of results. In RAG, where information retrieval is followed by text generation, chunking allows the system to search and process only the most relevant sections of content, improving both efficiency and accuracy. This approach ensures faster retrieval times, better handling of long-form documents, and more precise generation by focusing on contextually meaningful chunks rather than entire documents, ultimately enhancing the overall performance of LLMs in real-time applications.