There are several free alternatives to OpenAI that use the same API; which would make it possible to substitute OpenAI for one of those models in this extension. At least on paper. There is an open issue on the github repository requesting something like that.
So, it's not as clear cut. The general approach of using LLMs for this is not a bad one; LLMs are pretty good at this stuff.
Yes, but the API at the end is providing the core functionality. Simply swapping out one LLM model for another - let alone by a different company altogether - will completely change the effectiveness and usefulness of the application.
The premier open weight models don't even comparatively perform well on the public benchmarks compared to frontier models. And that's assuming at least some degree of benchmark contamination for the open weight models.
While I don't think they're completely useless (though its close), calling them fantastic replacements feels like an egregious overstatement of their value.
EDIT: Also wanted to note that I think this becomes as much an expectations-setting exercise as it is evaluation on raw programming performance. Some people are incredibly impressed by the ability to assist in building simple web apps, others not so much. Experience will vary across that continuum.
One would hope, that since the problem these models are trying to solve is language modeling, they would eventually converge around similar capabilities
Their interfacing software __is__ open source; and, they're asking for your OpenAI api key to operate. I would expect / desire open source code if I were to use that, so I could be sure my api key was only being used for my work, so it's only my work that I'm paying for and it's not been stolen in some way.
My older brother who got me into coding learned to code in Assembly. He doesn't really consider most of my work writing in high level languages to be "coding". So maybe there's something here. But if I had to get into the underlying structure, I could. I do wonder whether the same can be said for people who just kludge together a bunch of APIs that produce magical result sets.
> But if I had to get into the underlying structure, I could.
How do you propose to get into the underlying structure of the OpenAPI API? Breach their network and steal their code and models? I don't understand what you're arguing.
> How do you propose to get into the underlying structure of the OpenAPI API?
The fact that you can’t is the point of the comment. You could get into the underlying structure of other things, like the C interpreter of a scripting language.
I think the relevant analogy here would be to run a local model. There are several tools to easily run local models for a local API. I run a 70b finetune with some tool use locally on our farm, and it is accessible to all users as a local openAI alternative. For most applications it is adequate and data stays on the campus area network.
I think the argument is that stitching things together at a high level is not really coding. A bit of a no true scotsmen perspective. The example is that anything more abstract than assembly is not even true coding, let alone creating a wrapper layer around an LLM
So, it's not as clear cut. The general approach of using LLMs for this is not a bad one; LLMs are pretty good at this stuff.