Free Developer Tool
RAG Document Chunker
Visualize how your text splits into chunks for RAG pipelines and vector databases. Configure chunk size, overlap, and chunking strategy — see color-coded results in real-time. 100% Browser-Based
Paste text above to see chunk visualization
How to Use This Tool
1. Paste Your Document
Paste any text — a README, blog post, API docs, legal document, etc. The tool accepts up to 100,000 characters.
2. Configure Chunking
Set the target chunk size in tokens, the overlap percentage between chunks, and the strategy that fits your document structure.
3. Inspect & Export
Click any colored span to inspect that chunk's token count and position. Export as JSON for direct use with LangChain, LlamaIndex, or your own vector ingestion pipeline.
Chunking Strategies Explained
Fixed Token Count
Splits text at exact character boundaries derived from the token target. Fast and predictable, but may cut sentences mid-way. Best for uniform text where boundary quality matters less than chunk size consistency.
Sentence Boundary
Accumulates sentences until approaching the token limit, then starts a new chunk at a sentence boundary. Preserves semantic meaning — ideal for Q&A datasets and conversational retrieval.
Paragraph Boundary
Respects double-newline paragraph breaks. Each chunk ends cleanly at a paragraph boundary. Great for articles, documentation, and structured prose where paragraphs are topically cohesive.
Recursive (Recommended)
The most sophisticated strategy. Tries paragraph boundaries first; oversized paragraphs are further split by sentence, then by fixed tokens as a last resort. Used by LangChain's default text splitter.
Strategy Quick Reference
| Strategy | Boundary | Best For | LangChain Equivalent |
|---|---|---|---|
| Fixed Token | Character offset | Embeddings, uniform data | CharacterTextSplitter |
| Sentence | . ! ? | Q&A, conversational | NLTKTextSplitter |
| Paragraph | \n\n | Articles, documentation | CharacterTextSplitter(\n\n) |
| Recursive | \n\n → . → fixed | General purpose (recommended) | RecursiveCharacterTextSplitter |
Common RAG Use Cases
Knowledge Base Search
Chunk internal wikis, support docs, and SOPs into 512-token segments with 10% overlap before embedding into Pinecone or Weaviate for semantic search.
Long Document Q&A
Use sentence-boundary chunking for legal contracts or research papers — each chunk stays semantically coherent so retrieved passages directly answer the query.
Code Documentation
Chunk API references and code examples with recursive strategy — class/function boundaries align naturally with paragraphs before falling back to fixed splits for large functions.
Build Production RAG Systems
From document ingestion to retrieval-augmented generation — we design and deploy production RAG pipelines with optimal chunking, embedding, and retrieval strategies tailored to your data.
Talk to Our AI Team