rag-chunk and adaptive-chunking
These tools are competitors, as both aim to identify optimal RAG chunking strategies for documents, with "messkan/rag-chunk" focusing on testing and benchmarking Markdown and "ekimetrics/adaptive-chunking" providing an automated selection mechanism for various document types.
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.
About adaptive-chunking
ekimetrics/adaptive-chunking
Adaptive Chunking: automatically select the best chunking method per document for RAG. Accepted at LREC 2026.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work