What inputs are required for the RAG Chunk Visualizer?

Paste text and adjust chunk size and overlap.

How does the RAG Chunk Visualizer work?

Slices text by character positions. Each new chunk advances by chunk size minus overlap.

What are the assumptions and limitations of the RAG Chunk Visualizer?

This is character-based chunking, not token-based or semantic splitting. It does not measure retrieval quality; overlap must be smaller than chunk size.

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RAG Chunk Visualizer

Visualize how your text splits into vector embeddings.

Options

Chunk Size100

Overlap20

Input Source

Generated Chunks (0)

Frequently Asked Questions

What is RAG chunking?

Retrieval-Augmented Generation (RAG) requires splitting documents into smaller "chunks" before embedding them into a vector database. The chunk size directly affects retrieval quality.

Why does overlap matter?

Overlap ensures that a sentence split between two chunks is still retrievable. Without overlap, queries matching content at chunk boundaries may fail to find relevant results.

What is a good chunk size?

It depends on the use case. For Q&A, 200-500 characters is common. For summarization, 1000+ works better. Experiment with your specific content to find the optimal balance.

Characters vs Tokens?

This tool uses character-based chunking for simplicity. In production, consider token-based chunking to match your embedding model's limits (e.g., 512 tokens for some models).

What is semantic chunking?

Advanced RAG pipelines use "semantic chunking" which splits text by meaning (paragraphs, sections) instead of fixed sizes. Libraries like LangChain offer this out of the box.

Using RAG Chunk Visualizer

Explore how fixed-size chunks and overlap divide source text for retrieval.

What to enter: Paste text and adjust chunk size and overlap.
How it works: Slices text by character positions. Each new chunk advances by chunk size minus overlap.
Assumptions and limits: This is character-based chunking, not token-based or semantic splitting. It does not measure retrieval quality; overlap must be smaller than chunk size.