Chunk Visualizer

# Introduction↵
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Retrieval-augmented generation works best when documents are split into coherent chunks.↵
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## Why chunking matters↵
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Embeddings capture local meaning. Oversized chunks dilute signal; tiny chunks lose context.↵
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### Overlap↵
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Overlap preserves continuity across boundaries so answers that span two sections still retrieve well.↵
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## Markdown headers↵
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Header-aware splitters keep sections intact when possible, then fall back to size limits.↵

• #0[0, 104)104 chars~20 tok

  # Introduction
  
  Retrieval-augmented generation works best when documents are split into coherent chunks.

• #1[74, 194)120 chars~25 tokoverlap≈30

  re split into coherent chunks.## Why chunking matters
  
  Embeddings capture local meaning. Oversized chunks dilute signal;

• #2[164, 220)56 chars~12 tokoverlap≈30

  versized chunks dilute signal; tiny chunks lose context.

• #3[190, 310)120 chars~23 tokoverlap≈30

  nal; tiny chunks lose context.### Overlap
  
  Overlap preserves continuity across boundaries so answers that span two secti

• #4[280, 334)54 chars~10 tokoverlap≈30

  so answers that span two sections still retrieve well.

• #5[304, 424)120 chars~22 tokoverlap≈30

   sections still retrieve well.## Markdown headers
  
  Header-aware splitters keep sections intact when possible, then fall 

• #6[394, 445)51 chars~12 tokoverlap≈30

  tact when possible, then fall back to size limits.