django-vitevue VS doccano

A modern alternative to DRF to build apis in Django is django-ninja. It is very simple to use and it takes advantage of the Pydantic schemas for validation and provides an auto-generated api doc. It is less complex than DRF. I recently made a template repo using this stack. It includes Django forms support in the Vuejs frontend. The Django config was made using django-vitevue that can help configuring a Vitejs frontend quickly.

The django-vitevue package helps configuring a Vitejs frontend for Django. It's main feature is a management command to configure a Vitejs app to compile to Django templates and static files. It handles single page apps as well as partial Django templates and works with existing frontends

Good point. I would add that sometimes having a modern spa dev env makes sense, to take advantage of major improvements in frontend stacks like Typescript or hot module reload servers like Vitejs, and use drf or graphql on the Django backend side. Btw I made a package to help configuring a Vitejs frontend to compile to Django templates, if anyone interested by this approach: django-vitevue

You could be interested by django-vitevue if you want to use Vitejs for your frontend. This packages helps generating a Vitejs configuration to compile your modern components based frontend app to a Django template and static files. It can compile to a partial template that can be included in your pages like any other template. Note: this package has just been rewritten and released, it is brain new

Huh?

I wrote my own system for classifying a stream of texts in Python, I might Open Source it one of these days but I have to get it to the point where it is modular enough that I can customize it to do the particular things I want without subjecting people to my whims... I use it every day and I'm not afraid to demo it because it is rock solid.

My understanding is that my system would not be hard to adapt to work on images for certain kinds of tasks.

Pytorch is open source, Huggingface is open source. CUDA isn't. This is

https://labelstud.io/

and for annotating text spans there are so many open source tools

https://github.com/doccano/doccano

I worked for a company a few years back that built annotation tools for projects we sold to customers but never quite got to a polished general purpose annotator. Today there are an overwhelming number of companies in this space and products I never heard of, many of which are cloud based or paid. Looks like a gold rush to me.

I followed the guide to have doccano https://github.com/doccano/doccano setup in a notebook server in Kubeflow. It is running and the django connection is established, but it fails to connect with my localmachine so when I try to open the link, it does not respond. Is there a way to connect apps running on remove notebook servers to local in Kubeflow?

Why not just use the docker instructions on the GitHub page? https://github.com/doccano/doccano

doccano is built on a Django backend though I believe it uses extensive front end code for the annotation UI.

I worked at a place where we developed a system for doing this kind of tagging but it was for making training sets and there was no expectation that you could export the document from the system for normal use.

Quite a few NLP annotation systems are out there

https://prodi.gy/

https://brat.nlplab.org/

https://doccano.herokuapp.com/