chonkie and rag-chunk

These are complements: Chonkie is a production-ready ingestion library for RAG pipelines, while rag-chunk is a benchmarking CLI tool for evaluating and selecting optimal chunking strategies before deployment.

chonkie
80
Verified
rag-chunk
39
Emerging
Maintenance 22/25
Adoption 15/25
Maturity 25/25
Community 18/25
Maintenance 10/25
Adoption 9/25
Maturity 13/25
Community 7/25
Stars: 3,829
Forks: 256
Downloads:
Commits (30d): 82
Language: Python
License: MIT
Stars: 104
Forks: 5
Downloads:
Commits (30d): 0
Language: Python
License: MIT
No risk flags
No Package No Dependents

About chonkie

chonkie-inc/chonkie

🦛 CHONK docs with Chonkie ✨ — The lightweight ingestion library for fast, efficient and robust RAG pipelines

This is a lightweight tool for developers building Retrieval-Augmented Generation (RAG) applications. It takes various forms of text data, processes it by intelligently splitting it into smaller, meaningful parts (chunks), and then refines and embeds these chunks. The output is optimized text chunks ready to be stored in a vector database for efficient retrieval by large language models.

RAG development LLM application development text preprocessing vector database integration AI application engineering

About rag-chunk

messkan/rag-chunk

A Python CLI to test, benchmark, and find the best RAG chunking strategy for your Markdown documents.

This tool helps developers working with Retrieval-Augmented Generation (RAG) by optimizing how text documents are broken down into smaller, searchable pieces. You input your Markdown documents, and the tool evaluates various chunking methods, showing you which one performs best in terms of retrieval accuracy. It's designed for machine learning engineers and AI practitioners building or fine-tuning RAG systems.

RAG-system-development LLM-fine-tuning text-retrieval natural-language-processing knowledge-base-optimization

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