PyMuPDF VS semantic-kernel

This method is based on the use of the libraries markdown-it-py (conversion from markdown to html) and [PyMuPDF] https://github.com/pymupdf/PyMuPDF) (conversion from html to pdf). A small Python class links them together.

I think you might mean PyMuPDF (https://github.com/pymupdf/PyMuPDF), a Python library built on top of the MuPDF C library (https://mupdf.com/).

PyMuPDF and MuPDF are both available under dual open source AGPL and commercial licenses. They have been around for many years and are under continual development.

[Disclaimer, i work for Artifex, who wrote MuPDF and recently acquired PyMuPDF.]

There is an amazing sample on how to create your own LLM Service class to be used in Semantic Kernel. You can view the Sample here: https://github.com/microsoft/semantic-kernel/blob/3451a4ebbc9db0d049f48804c12791c681a326cb/dotnet/samples/KernelSyntaxExamples/Example16_CustomLLM.cs

This week, I had the chance to explore the SemanticKernel code base, particularly the core plugins. SemanticKernel comes equipped with these built-in plugins:

In this article we'll look at the high-level capabilities building AI orchestration systems in C# with Semantic Kernel, a rapidly maturing open-source AI orchestration framework.

I'm using Semantic Kernel (https://github.com/microsoft/semantic-kernel) and it's really nice. Makes building more complex workflows really simple without sacrificing control.

A bunch of examples (https://github.com/microsoft/semantic-kernel/blob/main/dotne...) for how to handle just about anything you need to do with OAI with a lot less boilerplate.

I haven't tried it but there's Microsoft semantic-kernel.

https://github.com/microsoft/semantic-kernel

Semantic Kernel github.com/microsoft/semantic-kernel

The need for efficient model routing has been a point of discussion in the community. Addressing this, I've submitted a pull request to Semantic-Kernel that introduces an automated multi-model connector.