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I like the idea of Jupyter supporting more languages, but isn’t the main issue that most AI tooling is deeply tied to Python? How do we solve that?


For the record, there are a million kernels for Jupyter: https://github.com/jupyter/jupyter/wiki/Jupyter-kernels


Don't fix something that's not broken


By not building tooling in Python.

llamacpp is a high performative open source solution capable of inference of large number of published LL models both in CPU and in GPU. It's written in C++.

It's easy to download and build in Windows or Linux.

It can be used as a command line tool, linked and used as a library from a variety of languages, including Python, or communicated with through a simple REST service which is also part of the same repo. It even has a simple Web frontend (built with React I believe) which allows you to use it for simple conversations (no bells and whistles).

And yet the author is using Ollama which itself is a wrapper around llamacpp (as most of them are) written in Python.

We're creating the problems that need soling.




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