The Make-or-Break Decision in RAG Systems: Choosing the Right Document Chunking Strategy

Author(s): MahendraMedapati

Originally published on Towards AI.

The way you split your documents could determine your RAG system’s success or failure

Picture this: You’ve built a RAG system for your company’s employee handbook. Everything seems perfect until your HR manager asks: “What’s our vacation accrual policy for part-time employees?”

The article addresses the importance of effective document chunking strategies in RAG (Retrieval-Augmented Generation) systems. It explores various methods, including fixed-size, semantic, and overlapping window chunking, discussing their advantages and disadvantages. By examining real-world scenarios, the author emphasizes how choosing the right chunking approach can significantly impact the accuracy and efficiency of information retrieval. Best practices include respecting natural document structures, maintaining context, and continuously optimizing based on specific use cases.

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Published via Towards AI