CodeGenX VS select2

GitHub link: https://github.com/DeepGenX/CodeGenX

Looks good, I am currently working on a similar open-source project called CodeGenX. Its a fine-tuned version of GPT-J. Can I ask how long this took to train, and what hardware was used?

Hey Everyone!

We are delighted to announce the first version of CodeGenX. CodeGenX is a free and open-source code-generation system (similiar to Github Copilot) powered by a fine-tuned version of GPT-J.

You can find details for installation and instruction on usage here: https://docs.deepgenx.com. Our GitHub repository can be found here: https://github.com/DeepGenX/CodeGenX.

I think it is important to identify what CodeGenX can and cannot do, so we know what to expect. We have found that CodeGenX works well for common use cases which occur repeatedly in the training set. It understands context and outputs code with similar formatting to your previous code using the appropriate variables. But it does not shine in places where logical or mathematical computations are needed. This does not mean that it doesn't understand any logic or math, but just a weak point of the model.

Here are some links that have additional information:

Website: https://deepgenx.com

CodeGenX is an extension that will help you write your code better and faster, it uses a fine-tuned version of GPT-J to generate code that's readable and efficient. You can find more details and a guide on how to use CodeGenX on our website, if you're interested in the source code, you can take a look at the github repo. If you have any questions or feedback, you can contact us via discord or by replying to this post.

You can find details for installation and instruction on usage here: https://docs.deepgenx.com. Our GitHub repository can be found here: https://github.com/DeepGenX/CodeGenX.

Hope you're doing well. We (a group of volunteers) are currently working on an open-source project called CodeGenX. The project is a code generation extension for VS Code (similar to GitHub Copilot) based on a custom fine-tuned version of GPT-J. The problem is that most of us working on the project are Machine Learning Engineers/Data Scientists and do not have much experience in webdev.

Most people using react aren't building SPAs. Vue/React can be used the same way as jquery, which is to add enhanced UI functionality that server-side HTML views simply can't offer.

The best example is a multi-select box, or a searchable select box with autocomplete (what W3 calls the combobox pattern https://www.w3.org/WAI/ARIA/apg/patterns/combobox/) which in jquery was usually via https://select2.org/

For example, on my company website there's a timezone select box with are 151 options. Asking a user to simply scroll through 100+ to find theirs is annoying vs typing a few characters and hitting enter.

There's many examples of select boxes like that and there really is no static server-side way to solve this problem (I tried hard to think of one)... without creating a multi-page Wizard for what should be a single field on a larger form.

If you're building a SaaS product there are many highly-interactive components that demand JS and there's really no better mainstream solution atm than static-first sites with small "islands" of Vue/React style components (ideally with hydration) where interactivity is required.

People still abuse React/Vue of course, but the trend is 100% moving back to "mostly static" rather than slow SPAs and IMO JS-powered components are not never going away unless browsers start offering these complex components built-in.

I’m a fan of select2 (https://select2.org), it supports loading in data from a foreign source (API)

You could use a Select2() for the records which prevent the massive amount of data being transferred.

Sometimes I still import it for only one thing : select2 that depends on it. Does anyone have an alternative ? I'd love it

The traditional solution was to use ModelAdmin.raw_id_fields, a comma-delimited string of IDs in a text input. Many users found the interaction inelegant, and so ModelAdmin.autocomplete_fields with live search integration with Select2 was added in Django 2.0.

The module django-extensions has a searchable select box widget. There are others using Select2 as well.