webwright
chonkie
| webwright | chonkie | |
|---|---|---|
| 3 | 3 | |
| 40 | 2,845 | |
| - | - | |
| 9.0 | 9.8 | |
| 3 months ago | about 1 month ago | |
| Python | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
webwright
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DeepRAG: Thinking to Retrieval Step by Step for Large Language Models
https://github.com/MittaAI/webwright
Let me know if you want to go over the code or want to discuss what works and what doesn’t. We had a loop on the action/function call “pipeline” but I changed it to just test if there was a function call or not and then just keep calling.
- Devin is now generally available
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Artifacts are now generally available
Webwright, like some other similar tools, will build and run code in a terminal or container. Just ask it to do a Mandelbrot set. We're currently working on adding ChromaDB to it for history and abstracting the LLM class to support Ollama.
https://github.com/MittaAI/webwright
chonkie
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Chunking your data for RAG
The Textractor extracts chunks of text from files and the Embeddings takes those chunks and builds an index/database. We'll use a late chunker backed by Chonkie.
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DeepRAG: Thinking to Retrieval Step by Step for Large Language Models
Semantic chunking is where I would start with now. Also check this out: https://github.com/chonkie-ai/chonkie
- Show HN: Chonkie – A Fast, Lightweight Text Chunking Library for RAG
What are some alternatives?
semantifly
rag-demystified - An LLM-powered advanced RAG pipeline built from scratch
open-webui - User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
denser-retriever - An enterprise-grade AI retriever designed to streamline AI integration into your applications, ensuring cutting-edge accuracy.
nango - A single API for all your integrations.
TalkWithYourFiles - An LLM GUI application; enables you to interact with your files, offering dynamic parameters that can modify response behavior during runtime.