GiovanniPasq/chunky

Validate, visualize, edit, and export chunks for RAG pipelines.

32
/ 100
Emerging

This tool helps AI engineers and data scientists build more reliable Retrieval-Augmented Generation (RAG) applications by ensuring the quality of source documents. You input PDFs and get out validated Markdown and perfectly structured data chunks, ready for your vector database. It's designed for anyone setting up RAG pipelines who needs to visually inspect and refine their document processing.

Use this if you are building RAG applications and frequently encounter issues with document conversions or sub-optimal chunking leading to poor AI responses.

Not ideal if you are looking for a fully automated, hands-off RAG solution without needing to visually inspect and manually adjust document processing steps.

RAG-pipeline-development document-processing data-preparation LLM-engineering AI-application-development
No Package No Dependents
Maintenance 10 / 25
Adoption 6 / 25
Maturity 11 / 25
Community 5 / 25

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Stars

17

Forks

1

Language

Python

License

MIT

Last pushed

Mar 12, 2026

Commits (30d)

0

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curl "https://pt-edge.onrender.com/api/v1/quality/rag/GiovanniPasq/chunky"

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