open-interpreter VS llm

I think openinterpreter [1] were one of the first teams in this space along with shroominic code interpreter api and afaik they started with selenium but have expanded to do a lot more os level work but wonder if having a more narrow specialization could help these newer projects be better at the one thing they are focused on.

[1] https://openinterpreter.com/

I taught https://github.com/KillianLucas/open-interpreter how to use https://github.com/ferrislucas/promptr

Then I asked it to add a test suite to a rails side project. It created missing factories, corrected a broken test database configuration, and wrote tests for the classes and controllers that I asked it to.

I didn't have to get involved with mundane details. I did have to intervene here and there, but not much. The tests aren't the best in the world, but IMO they're adding value by at least covering the happy path. They're not as good as an experienced person would write.

I did spend a non-trivial amount of time fiddling with the prompts I used to teach OI about Promptr as well as the prompts I used to get it to successfully create the test suite.

The total cost was around $11 using GPT4 turbo.

I think in this case it was a fun experiment. I think in the future, this type of tooling will be ubiquitous.

My understanding is that ShellGPT aims to be a complete OS assistant. It's similar to Open Interpreter (https://github.com/KillianLucas/open-interpreter).

Shelly is a mini tool at the moment that only generates and executes commands for you.

https://github.com/KillianLucas/open-interpreter Both OpenAI and Local

Yeah there's a program called openinterpreter, It works beautifully. https://openinterpreter.com/

That's a great use case, you might be able to do this if you've got a copy and paste on the command line with

https://github.com/simonw/llm

In between. An alias like pdfwtf translating to "paste | llm command | copy"

I added support for this model to my LLM CLI tool via a new plugin: https://github.com/simonw/llm-command-r

So now you can do this:

    pipx install llm

If you're willing to use the CLI, Simon Willison's llm library[0] should do the trick.

[0] https://github.com/simonw/llm

I'm not thrilled about https://github.com/GoogleCloudPlatform/localllm/blob/main/ll... calling their Python package "llm" and installing "llm" as a CLI command, when my similar https://llm.datasette.io/ project has that namespace reserved on PyPI already: https://pypi.org/project/llm/

I've been gleefully exploring the intersection of LLMs and CLI utilities for a few months now - they are such a great fit for each other! The unix philosophy of piping things together is a perfect fit for how LLMs work.

I've mostly been exploring this with my https://llm.datasette.io/ CLI tool, but I have a few other one-off tools as well: https://github.com/simonw/blip-caption and https://github.com/simonw/ospeak

I'm puzzled that more people aren't loudly exploring this space (LLM+CLI) - it's really fun.

Seems nice if you're using c# or java. It also supports python, but for that Simon's llm library is nice because he designed it as both a library and a command line tool: https://github.com/simonw/llm