I’m an IT professional and I have no idea how to begin answering that request! Pose that question verbatim to a dozen random people[1] and I guarantee you that you’ll get zero answers.
Also, I find it hilarious that sed and awk are so counterintuitive that not even the AIs can do useful things with them. The same AIs that speak Latin, and can explain quantum mechanics.
[1] I mean specifically not random Silicon Valley coworkers. Go talk to random relatives and the barista at the cafe.
Make the component beautiful with good spacing, elevation etc. Use Grid/Card components."
Final result: https://res.cloudinary.com/dksmi6x98/image/upload/v168527409...
However if the problem is stated in a way that it has to think through derivative of it's solution: that is generate some code that generates some other code which behaves in a certain way, it fails miserably. I'm not sure why. The problem I stated in current thread which it failed on I have tried multiple prompts to make it understand the problem but unfortunately nothing worked. It's as if it can do first level but but not second level abstraction.
Also, in general we attempt to make these models as economically efficient as possible at this point because of the extreme lack of excess computing power to run these things. You can't have it spending the next 30 minutes thinking in loops about the problem at hand.
You can get them to talk through the problem, build parts, test things, etc.
Also, this is a horrible problem to solve with awkward tools. Why is your code file to large to cat???
Anyways posting this here isn't to get this particular problem solved. It is to see if there is a prompt that can solve it. And this is the only problem I found it not able to solve. It's not like it doesn't know about sed/awk/grep or other Linux tools, it is an expert on most of the common options involving them. My guess is there is something going on with this prompt that just breaks it's 'though patterns' for the lack of a better word :)
These are command line tools though, not piping it into the llm.
My point though was more about giving it space to reason. It's very important for good results on more complex tasks.
Prerequisite (for you the human)> You have a file at src/SampleReactComponent.jsx that has below simple react component: const SampleReactComponent = (props) => {
return (<></>); };export default SampleReactComponent;
********** Prompt for GPT4: I'm at my project root working on a reactjs project. Update the component in src/SampleReactComponent.jsx file by adding a new const variable after the existing variables. You cannot use cat command as the file is too big. You can use grep with necessary flags and sed to achieve the task. I'll provide you the output of each command that you generate. *************
That's it. It would do any complex modification on fully provided data (included in the prompt) but something like above where it has to build a model from secondary prompts will totally fall apart.