Chonkie v1.4 is here. An open-source AI ingestion framework built for smarter document parsing and RAG pipelines. This update introduces Pipelines for retrieval workflows, Chefs for cleaning messy data, TableChunkers for structured markdown, and Handshakes to connect with

Matt Pocock Chonkie recently added full TS support to their SDK (they went Python first too).

Come find us at the MIT AI conference! Grab a hat and stickers 🦛❤️

🎉 3,000🌟 for Chonkie! Huge thanks to the amazing community for all the support—here's to many more milestones together! #Chonkie #opensourcecode #Python

The Rag and Rug Company Of San Francisco

And we’re just getting started :)

a millie a millie a millie a millie a miilie

I'm glad to announce that we reached over 1,000,000 downloads at Chonkie🔥 our library is growing, we reached over 3,000 stars on github, more than 250 repos are dependent on Chonkie and have been used by people from big tech companies like openai, microsoft and several others

I recently had to pick a RAG stack for an MVP, so I wanted something super hands off. I want control on the chunking strategy and then everything else might as well be a black box. I found Chonkie , but was a little skeptical. Booked a call with the founder, Shreyash Nigam,

Chonkie has crossed 1 million downloads! Developers worldwide are using Chonkie to ingest data into their AI applications. We're excited to keep building the best tools for connecting data to AI. Thanks to everyone who's been part of this journey. 🦛❤️

Stop the API ping-pong. 🏓 With the new Pipeline API, you can build complex multi-chunking and refinement flows in the UI and execute them with a single call. Everything is initialized server-side, meaning zero back-and-forth and significantly lower latency. ⚡️ One request.

Chonkie and Weaviate 1. Weaviate Handshake: Use Chonkie’s `MarkdownChef` to extract chunks and ingest them into Weaviate to search (github.com/weaviate/recip…)

Quality context right in your database