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Rahul Agarwal
Founder | Agentic AI... • 22h
6 Chunking Methods for RAG you should know. I’ve explained it in a simple, step by step way. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴? 1. Chunking means splitting large documents into smaller pieces. 2. Helps LLMs search and understand data better. 3. Essential for Retrieval-Augmented Generation (RAG). 𝗦𝘁𝗲𝗽 1: 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴 • Split content based on meaning, not just size. • Group sentences that talk about the same idea. • Uses embeddings to detect topic changes. • Produces high-quality chunks but costs more compute. Best for: Meaning-heavy content where context matters. 𝗦𝘁𝗲𝗽 2: 𝗥𝗲𝗰𝘂𝗿𝘀𝗶𝘃𝗲 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴 • Break text using a hierarchy (paragraphs → sentences → words). • Ensures chunks stay within token limits. • Works well for most text documents. Best for: General-purpose RAG pipelines. 𝗦𝘁𝗲𝗽 3: 𝗦𝗲𝗻𝘁𝗲𝗻𝗰𝗲-𝗟𝗲𝘃𝗲𝗹 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴 • Split text strictly at sentence boundaries. • Combine multiple sentences into one chunk. • Preserves natural language flow. Best for: Articles, blogs, and readable text. 𝗦𝘁𝗲𝗽 4: 𝗣𝗮𝗿𝗲𝗻𝘁–𝗖𝗵𝗶𝗹𝗱 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴 • Store small chunks for search accuracy. • Return larger parent chunks for full context. • Balances precision and completeness. Best for: Question answering systems. 𝗦𝘁𝗲𝗽 5: 𝗔𝗦𝗧-𝗔𝘄𝗮𝗿𝗲 𝗖𝗼𝗱𝗲 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴 • Split code using its structure (functions, classes). • Avoids breaking logical blocks. • Requires language-specific parsers. • Keeps code clean and unbroken. Best for: Codebases and developer tools. 𝗦𝘁𝗲𝗽 6: 𝗛𝘆𝗯𝗿𝗶𝗱 𝗖𝗵𝘂𝗻𝗸𝗶𝗻𝗴 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆 • Choose chunking method based on content type. 1. Code → AST-aware 2. PDFs → Page-based 3. Text → Recursive or Semantic • Delivers the highest retrieval accuracy. Best for: Production-grade AI systems. ✅ 𝗜𝗻 𝘀𝗵𝗼𝗿𝘁 • 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 → splits by meaning • 𝗥𝗲𝗰𝘂𝗿𝘀𝗶𝘃𝗲 → splits by structure (most common) • 𝗣𝗮𝗿𝗲𝗻𝘁–𝗖𝗵𝗶𝗹𝗱 → small search, big context • 𝗦𝗲𝗻𝘁𝗲𝗻𝗰𝗲-𝗹𝗲𝘃𝗲𝗹 → simple and natural • 𝗔𝗦𝗧-𝗮𝘄𝗮𝗿𝗲 → best for code • 𝗛𝘆𝗯𝗿𝗶𝗱 → smart combination of all Test with real queries, adjust chunk size, monitor performance, and continuously improve your RAG pipeline. ✅ Repost for others who can benefit from this.
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