| Tutorial | Description | Try it |
|---|---|---|
| Recursive Chunking for PDF/Markdown Documents | A quick look at how you can use Chonkie's RecursiveChunker to chunk your PDF/Markdown documents and build a RAG pipeline over it! |  |
| SlumberChunker with OpenRouter | A quick look at how you can use the SlumberChunker with models from OpenRouter with the help of the OpenAIGenie! |
|
| RecursiveChunker with JSON Export | Demonstrates how to chunk text with RecursiveChunker and export to JSON/JSONL formats using JSONPorter, including metadata enhancement and data integrity verification. |  |
| Gemini Embeddings with Recursive Chunking | Learn how to use Google's Gemini embedding models with Chonkie's RecursiveChunker for high-quality text embeddings and similarity analysis! | |
| PostgreSQL + pgvector with PgvectorHandshake | Complete example showing how to store and search chunks in PostgreSQL with pgvector using the PgvectorHandshake and vecs library, including metadata filtering and vector indexing. | |
| Pinecone Agentic RAG | Example demonstrating how to use Chonkie's PineconeHandshake in an agentic RAG pipeline | |
| Qdrant Handshake for TinyStories | A tutorial showing how to connect Chonkie with Qdrant using the QdrantHandshake to store and search TinyStories embeddings. | |
| LlamaIndex + Chonkie: Document Q&A with Recursive Chunking | Learn how to use Chonkie as a native LlamaIndex node parser. Build a simple RAG over a Wikipedia article using Chonkie's Recursive Chunker | |
Chonkie is proud to power a diverse ecosystem of projects and integrations across the AI and ML landscape. Our lightweight, flexible architecture makes it easy to integrate Chonkie into your existing workflows and tools.
Want to add your integration? Simply raise an issue and we'll help you get started! Once approved, your integration will be featured here.
| Integration | Description | Repository |
|---|---|---|
| ⚡️ FlashRAG | A Python toolkit for the reproduction and development of Retrieval Augmented Generation (RAG) research. |  |
| 📄 Txtai | All-in-one embeddings database for semantic search, LLM orchestration and language model workflows | |
| 🏄 SurfSense | Highly Customizable AI Research Agent just like NotebookLM or Perplexity, connected to external sources such as search engines (Tavily), Slack, Notion, YouTube and more. | |
| 🌬️ Airweave | Airweave is a tool that lets agents semantically search any application or database. It's MCP compatible and seamlessly connects any app, database, or API, to transform their contents into agent-ready knowledge. | |
| 🐊 ingest-anything | ingest-anything is a python package aimed at providing a smooth solution to ingest non-PDF files into vector databases, given that most ingestion pipelines are focused on PDF/markdown files. | |
| Add your integration here! | Share your Chonkie integration with the community | |
Share your knowledge and experiences with Chonkie! Whether it's a blog post, video tutorial, or technical deep-dive, we'd love to feature your content here.
| Type | Title | Author | Description |
|---|---|---|---|
| Blog | Chonkie: a lightweight RAG text chunking library | Aishare | A quick look at Chonkie, a lightweight RAG text chunking library. |
| Blog | Text Chunking for RAG systems with Chonkie | Toni Ramchandani | Chonkie: Revolutionizing Text Chunking for Efficient RAG Applications |
| Video | Chonkie - RAG Chunking Library - Easy Local Installation and Testing | Fahd Mirza | A quick walkthrough of how to install Chonkie and test it out for yourself! |
| Blog | Easy Late-Chunking with Chonkie | Michael Ryaboy | This blog post is a quick look at how you can use Chonkie's LateChunker to chunk your documents and build a search pipeline over it with KDB.AI! |
| Blog | Ingest (almost) any non-PDF document in a vector database, effortlessly | Clelia (Astra) Bertelli | Introduction to the ingest-anything library, a tool that allows you to ingest (almost) any non-PDF document in a vector database, effortlessly. |
| Blog | Semantic Chunking PDFs In The Cloud With Chonkie | Michael Ryaboy | Utilizing Chonkie Cloud to help frontend engineers to use semantic chunking and build RAG pipelines easily |
| Project | Chunk Explorer | Ruslan Bel'kov | A powerful tool for exploring and visualizing different text chunking strategies, designed to help you understand how various text splitters work with different types of content. |
| Project | RAGHub | Andrew Jang | A living collection of new and emerging frameworks, projects, and resources in the Retrieval-Augmented Generation (RAG) ecosystem |
Have content to share? Open an issue with your resource and we'll get it added to the cookbook!
Want to add your project or integration to the cookbook? Check out our contribution guidelines!
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