LAB · RAG

Chunking Workbench

Compare chunk size, overlap, and context loss on a real document before indexing it.

Suggested time: 15 min
Output artifact: An explainable chunking strategy with statistics and inspectable fragments.
Privacy: The document stays in local memory and never leaves the page.

OUTPUT

Complete the fields and run the tool.

Local educational tool. Validate every result before production use.

When to use it

Chunking lab

Use it before indexing a corpus or when answers lose context across fragment boundaries.

How to use it well

1
Enter a real case without secrets or personal data.
2
Run, inspect, and challenge the assumptions; the output is not automatic truth.
3
Save the artifact in your project and turn it into a reviewable test or decision.

Related foundations

Retrieval Engineering

6 min

03 — Chunking Strategies

The chunk is the atomic unit of the entire system: it is what gets embedded, what gets indexed, what gets retrieved, and what the LLM sees. Poor chunking imposes a quality ceiling that no other component can surpass. The

Open foundation20 min

Lab 03 — Compare chunking with a retrieval metric

Localized walkthrough. Run the canonical public lab locally and preserve the result as evidence.

Open foundation