reframe VS litebox

NNext.ai » Software Engineer » Python » Full-time » NY, NY, USA » Remote

At [NNext.ai](http://NNext.ai) (read “Next.ai”), we are building building core infrastructure to simplify the process of building, deploying, and managing LLM-powered AI agents on tabular data, making it the most efficient solution available. NNext AI enables users to combine the power of Large Language Models (LLMs) like GPT with tools like the browser and Google Search, greatly increasing your productivity on workflows you once spent countless hours on. We are building a framework specialized for tabular data such as Spread sheets, Database Tables and CSVs, thereby taking advantage of the similarities and co-dependencies amongst data.

We are lean team of engineers looking for our first full time OSS contributor. Desirable experience includes distributed systems working with tools like Celery, Dash and Redis Streams. Visibility on Github is a huge plus. Show us previous OSS software you’ve contributed to or public personal projects with significant usage.

Website: https://nnext.ai

Github: https://github.com/nnextai/aigent

Email: [email protected]

https://github.com/nnextdb/nnext/blob/main/FAQs.md Q: How does this differ from Faiss, ScaNN and Annoy?

What’s NNext? [Say “Next”] NNextDB is a blazingly fast ⚡️, open-source 📖, (vector) neural search 🔎 engine for building delightful AI Apps 🦾. Github: https://github.com/nnextdb/nnext Like what you see? Please give us a Star 🤩. Applications Vector search is a key concept in modern machine learning systems. It’s the technology behind

These things mostly work by having some vision model, chopping it off somewhere in the middle and using that layer as an "embedding" for your image. Then you look for images that have embeddings which are close together (normally in the sense of Euclidean distance, e.g.)

Code Link: https://github.com/nnextdb/nnext

NNextDB - a blazing fast, open source, vector search database for building AP applications.

https://github.com/nnextdb/nnext

After playing with ANNOY and FAISS for a little while, I hit exactly that problem. I ended up writing two Python libraries for fast "object search by metadata" - FilterBox and LiteBox. They are both designed to complement vector search, as they only deal with the metadata portion of the objects and leave the vectors alone.

Yep. I even wrote a container called LiteBox to make it quicker syntax-wise.