attercop 0.2.0

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attercop

Your friendly, micro command line LLM query generation tool!

Overview

attercop is a micro Python tool that generates command prompts via an LLM provider. It uses the OpenAI API to map natural language queries to a command or sequence of commands, emphasizing usage of standard GNU tools. The example I use in the GPT query is:

$ attercop "List all the files in this directory, filtering out the ones that are not directories, and then sort them by size, largest first."
(1/1) ls -l | grep ^d | sort -k5 -n -r

It then lets you cycle through multiple options with Tab if the prompt is somewhat ambiguous, and either confirm and run with y or Enter, copy to clipboard with c, or outright reject the command with q, Ctrl+C or Ctrl+D.

Installation

The package is now available on PyPI, so as long as you're running Python >=3.10, you can install it with pip:

pip install attercop

You will need to set the environment variable OPENAI_API_KEY to your personal OpenAI API key. You can get one here - as of January 2023, as a new member you will get plenty of free credits to play with. For more on pricing you can see their page here.

Usage

Once you've installed, you can just run the attercop command:

$ attercop "Find all files in this and subdirectories ending with the extension .txt"
(1/1): find . -name "*.txt"

It will hit the OpenAI API and come back with one of several prompts, depending on the max_prompts parameter. You can cycle through these with tab, select one for execution with enter or 'y', or hit 'q' or Ctrl-C to quit.

Command	Key
Cycle Command	Tab
Execute	y | Enter
Copy to Clipboard	c
Reject	q | Ctrl+C | Ctrl+D

For the full list of options, see attercop --help:

$ attercop --help
usage: attercop [-h] [-v] [-n NUM_PROMPTS] [-t TEMPERATURE] [-m MAX_TOKENS] [-M MODEL] [-K API_KEY] [-s SHELL] prompt

Generate a command or chain of shell commands from a natural language prompt. Once generated, you can cycle through commands with tab, accept a command with enter or y, copy to the clipboard with c, or
quit with q.

positional arguments:
  prompt                The English-language prompt to use for the GPT completion.

options:
  -h, --help            show this help message and exit
  -v, --verbose         Prefer verbose flags for the generated command, ie. `--help` instead of `-h`. Defaults to False, though it won't explicitly ask for short flags.
  -n NUM_PROMPTS, --num-prompts NUM_PROMPTS
                        The maximum number of alternative prompts to generate. Defaults to 3.
  -t TEMPERATURE, --temperature TEMPERATURE
                        Higher values will result in more diverse completions, but lower values will generally result in more sensible ones. Defaults to 0.
  -m MAX_TOKENS, --max-tokens MAX_TOKENS
                        The maximum number of tokens to generate per prompt. Defaults to 100.
  -M MODEL, --model MODEL
                        The GPT model to use. Defaults to text-davinci-003, the latest and most powerful model generally available.
  -K API_KEY, --api-key API_KEY
                        Manually specify an OpenAI API key to use. If none provided, will default to the OPENAI_API_KEY environment variable.
  -s SHELL, --shell SHELL
                        The shell to use for the generated command, ie. bash, zsh, fish... If none provided, will look for a SHELL environment variable if available, or otherwise default to bash.

What about other LLM providers?

I would definitely prefer this tool to be agnostic to the LLM provider. If you want to add support for another provider, please open an issue or a pull request! Also feel free to open an issue if you have any other suggestions or feedback.