A fast, lightweight and easy-to-use Python library for splitting text into semantically meaningful chunks.

🍱 semantic-chunking ⇢ semantically create chunks from large document for passing to LLM workflows

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

Chunk smarter, not harder — built for LLMs, RAG pipelines, and beyond.

A sentence splitting (sentence boundary disambiguation) library for Go. It is rule-based and works out-of-the-box.

JChunk is a lightweight and flexible library designed to provide multiple strategies for text chunking within Java applications

A collection of custom n8n nodes for enhanced document processing, text splitting, and embeddings generation

An exploration of text splitting and chunking in JavaScript

A web app that allows users to upload PDFs and interact with them through a Q&A interface. The application extracts text from PDFs, generates embeddings, stores them in a FAISS database, and retrieves relevant information to provide context-aware answers using a large language model .

A smart C# text splitting library that intelligently chunks text while preserving semantic boundaries. Uses a hierarchical approach with configurable overlap and detailed metadata.

An intelligent chatbot that allows users to upload text-based Ayurveda PDFs and ask questions based on the content using RAG (Retrieval-Augmented Generation) combining semantic search and LLM-based responses.

Text splitting example using Tiktoken

LangChain is a framework, which is very helpful and easy to build applications based on available Large Language Models.

I built a News Research Tool with Streamlit and LangChain that fetches news articles from URLs, processes them with text splitting and embeddings, and stores them in a FAISS vector DB. Users can query articles via a RetrievalQA chain to get precise, source-backed insights—showcasing my skills in LLMs and vector search.

Specialized markdown text splitter - part of LEDAA project's data ingestion pipeline for RAG.

This is an experiment in learning langchain, pinecone and stuff, don't mind

Matching strings between lists based on length​

A bot that will leverage LangChain and a large language model (LLM) to answer questions based on content from loaded PDF

An exploration of advanced text splitting strategies in LangChain for RAG, from basic character splitting to state-of-the-art semantic chunking.