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*The Art of Chunking in AI Systems: Foundation and Core Techniques* is a comprehensive guide to chunking in Retrieval-Augmented Generation (RAG) systems. It covers fixed-length, character-based, token-based, sliding-window, document-specific, semantic, code-aware, hierarchical, and agentic chunking approaches. The book discusses the principles, advantages, limitations, implementation considerations, and practical applications of these techniques, with guidance for selecting and evaluating chunking strategies for real-world AI systems.
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