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Rahul Agarwal
Founder | Agentic AI...ย โขย 21d
6 Chunking Methods for RAG you should know. Iโve explained it in a simple, step by step way. ๐ช๐ต๐ฎ๐ ๐ถ๐ ๐๐ต๐๐ป๐ธ๐ถ๐ป๐ด? 1. Chunking means splitting large documents into smaller pieces. 2. Helps LLMs search and understand data better. 3. Essential for Retrieval-Augmented Generation (RAG). ๐ฆ๐๐ฒ๐ฝ 1: ๐ฆ๐ฒ๐บ๐ฎ๐ป๐๐ถ๐ฐ ๐๐ต๐๐ป๐ธ๐ถ๐ป๐ด โข Split content based on meaning, not just size. โข Group sentences that talk about the same idea. โข Uses embeddings to detect topic changes. โข Produces high-quality chunks but costs more compute. Best for: Meaning-heavy content where context matters. ๐ฆ๐๐ฒ๐ฝ 2: ๐ฅ๐ฒ๐ฐ๐๐ฟ๐๐ถ๐๐ฒ ๐๐ต๐๐ป๐ธ๐ถ๐ป๐ด โข Break text using a hierarchy (paragraphs โ sentences โ words). โข Ensures chunks stay within token limits. โข Works well for most text documents. Best for: General-purpose RAG pipelines. ๐ฆ๐๐ฒ๐ฝ 3: ๐ฆ๐ฒ๐ป๐๐ฒ๐ป๐ฐ๐ฒ-๐๐ฒ๐๐ฒ๐น ๐๐ต๐๐ป๐ธ๐ถ๐ป๐ด โข Split text strictly at sentence boundaries. โข Combine multiple sentences into one chunk. โข Preserves natural language flow. Best for: Articles, blogs, and readable text. ๐ฆ๐๐ฒ๐ฝ 4: ๐ฃ๐ฎ๐ฟ๐ฒ๐ป๐โ๐๐ต๐ถ๐น๐ฑ ๐๐ต๐๐ป๐ธ๐ถ๐ป๐ด โข Store small chunks for search accuracy. โข Return larger parent chunks for full context. โข Balances precision and completeness. Best for: Question answering systems. ๐ฆ๐๐ฒ๐ฝ 5: ๐๐ฆ๐ง-๐๐๐ฎ๐ฟ๐ฒ ๐๐ผ๐ฑ๐ฒ ๐๐ต๐๐ป๐ธ๐ถ๐ป๐ด โข Split code using its structure (functions, classes). โข Avoids breaking logical blocks. โข Requires language-specific parsers. โข Keeps code clean and unbroken. Best for: Codebases and developer tools. ๐ฆ๐๐ฒ๐ฝ 6: ๐๐๐ฏ๐ฟ๐ถ๐ฑ ๐๐ต๐๐ป๐ธ๐ถ๐ป๐ด ๐ฆ๐๐ฟ๐ฎ๐๐ฒ๐ด๐ โข Choose chunking method based on content type. 1. Code โ AST-aware 2. PDFs โ Page-based 3. Text โ Recursive or Semantic โข Delivers the highest retrieval accuracy. Best for: Production-grade AI systems. โ ๐๐ป ๐๐ต๐ผ๐ฟ๐ โข ๐ฆ๐ฒ๐บ๐ฎ๐ป๐๐ถ๐ฐ โ splits by meaning โข ๐ฅ๐ฒ๐ฐ๐๐ฟ๐๐ถ๐๐ฒ โ splits by structure (most common) โข ๐ฃ๐ฎ๐ฟ๐ฒ๐ป๐โ๐๐ต๐ถ๐น๐ฑ โ small search, big context โข ๐ฆ๐ฒ๐ป๐๐ฒ๐ป๐ฐ๐ฒ-๐น๐ฒ๐๐ฒ๐น โ simple and natural โข ๐๐ฆ๐ง-๐ฎ๐๐ฎ๐ฟ๐ฒ โ best for code โข ๐๐๐ฏ๐ฟ๐ถ๐ฑ โ smart combination of all Test with real queries, adjust chunk size, monitor performance, and continuously improve your RAG pipeline. โ Repost for others who can benefit from this.
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