Can't speak for this tool yet, but ChatGPT has been great for this use case. Sometimes a tool doesn't have a man page, has hard to navigate docs, or whatever, "What does $flag mean in $tool" tends to work (when it doesn't hallucinate something totally wrong).

One recent example: "what does -w do on curl" .. not a single top 10 result on Google mentions it in the context, but GPT3.5 nails it in two seconds complete with a working example. I know "-w" is interpreted by Google in a special way, but frankly given the obvious context I shouldn't need to know how Google works. (Through experience I also know https://explainshell.com/explain?cmd=curl+-w will do a good job, but ChatGPT actually provides a working example which is even better.)

That said, I do think you need a good critical eye to use LLMs in this context. It's like relying on a calculator. You still need mental math skills to know that 91 * 10 can't equal 2511. Similarly, when GPT starts hallucinating, it helps if you have a high sensitivity to smelling it out.

I use an alternative that just directly calls OpenAI using my API key. I have it mapped to the command `ai` and it works really really well. So far I've found no need for any intermediary or fancy features. It just shows the command with a (y/[N]) prompt and I can choose to run it or not.

I use the first tagged version of `aicmd` before it was given an unneeded intermediary: https://github.com/atinylittleshell/aicmd/tree/v1.0.2

Would really like it if ML projects would declare upfront if you're using cloud models or local ones. A lot of work policies bar us from using externally generated code or inputting business data into external systems.

(as it happens, this one hits the cloud)

It's not a local model. It queries some endpoint on someone else's computer.

Loving it! Works nicely for k8s:

  (base)   ~ g get the image ids of all pods running in all namespaces in kubernetes
    kubectl get pods --all-namespaces -o jsonpath="{..imageID}"
  sha256:b19406328e70dd2f6a36d6dbe4e867b0684ced2fdeb2f02ecb54ead39ec0bac0 
  sha256:b19406328e70dd2f6a36d6dbe4e867b0684ced2fdeb2f02ecb54ead39ec0bac0

I recommend shell-gpt[1] for anyone with access to the OpenAI API. It works surprisingly well considering how simple it is. Be sure to browse the examples in the README.

[1] https://github.com/TheR1D/shell_gpt

newbie question.

Not to make this a debug thread but this is what I get when I try out gorilla

> gorilla I want to find my ip address

/home/username/.local/lib/python3.10/site-packages/requests/__init__.py:102: RequestsDependencyWarning: urllib3 (1.26.7) or chardet (5.1.0)/charset_normalizer (2.0.7) doesn't match a supported version! warnings.warn("urllib3 ({}) or chardet ({})/charset_normalizer ({}) doesn't match a supported " Traceback (most recent call last): File "/home/username/.local/bin/gorilla", line 8, in <module> sys.exit(main()) File "/home/username/.local/lib/python3.10/site-packages/go_cli.py", line 128, in main user_id = get_user_id() File "/home/username/.local/lib/python3.10/site-packages/go_cli.py", line 76, in get_user_id assert user_id != "" AssertionError

Is this actually developed by UC Berkeley or just a project by one of their PhD students?

Maybe [GPTCache](https://github.com/zilliztech/GPTCache) can make it more attractive, because similar problems can be less expensive, and can also be responded to faster. Of course, the specific configuration needs to be based on real usage scenarios.

Hey HN! As one of the contributors and author of Gorilla, we want to express gratitude for your valuable feedback. The community's desire for a straightforward method to invoke Gorilla led to the development of this CLI tool. We appreciate your continued input, so please keep those suggestions coming!

Waiting for the LLM version of ye olden IRC hazing/trolling of: "oh you can fix that with rm -rf /"

Edit: Typo

We've gone full circle: efficient meta languages back to inefficient and ambivalent natural language.

Is it weird I'm kind of more interested in this included "go_questionary" library?

Hi HN, I'm one of the authors from Gorilla Project. Gorilla now presents in an CLI interface and you can interact with your laptop in English! Feedbacks and suggestions are very welcome!!

It runs in the terminal, so you can also CTRL-r it!

How does this compare with github-copilot-cli?

It’s very sketchy that they use stderr and queries for training.

Don’t pass anything sensitive into this program!

Giving anyone who can type full system admin abilities without any need for training?

What could go wrong?

I would encourage authors to update README with more representative examples.

very cool. But like many other uses of LLM it can hallucinate and/or produce a wrong result. For example I tried:

"gorilla dry run of brew upgrade"

And got a response that didn't work.

Geez, I don't understand most of the words in that headline...

Doesn't this violate the Gorilla glue's trademark?

goodbye Fig!