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I've been automating some of our team's most menial tasks and since we're in a corporate environment we don't have control over what is and isn't installed on o

I've been automating some of our team's most menial tasks and since we're in a corporate environment we don't have control over what is and isn't installed on our servers, so using bash is the sane default choice. None of the scripts it produced are incredible or whatever (the tasks being more menial than lohic-based), but considering the intricacies of bash and how often I just faceplant into them as an experienced sysadmin, if feel as though the ability to just say "write a script that compares a list of agents against every manager and outputs the ones not found anywhere" and have it output basically a working script first try is impressive.

comfypotato 3y ago
Here’s a paper that constitutes the state of the art in this domain in 2018. [1] They trained a model on a corpus, and the results were about 50% accurately executed commands. That’s only single commands (not complete scripts) and you couldn’t go back and forth with NL2Bash to fix mistakes. I think this is a great example of the strides of LLMs. It’s absolutely leaps and bounds ahead of what was unwieldily cutting edge just 5 years ago. https://homes.cs.washington.edu/~mernst/pubs/nl2bash-corpus-lrec2018.pdf https://homes.cs.washington.edu/~mernst/pubs/nl2bash-corpus-...