Show HN: Llm2sh – Translate plain-language requests into shell commands

llm2sh is a command-line utility that leverages Large Language Models (LLMs) to translate plain-language requests
into shell commands. It provides a convenient way to interact with your system using natural language.

Translates plain language requests into corresponding shell commands
Supports multiple LLMs for command generation
Customizable configuration file
YOLO mode for running commands without confirmation
Easily extensible with new LLMs and system prompts
Verbose mode for debugging

llm2sh uses OpenAI, Claude, and other LLM APIs to generate shell commands based on the user’s requests.
For OpenAI, Claude, and Groq, you will need to have an API key to use this tool.

OpenAI: You can sign up for an API key on the OpenAI website.
Claude: You can sign up for an API key on the Claude API Console.
Groq: You can sign up for an API key on the GroqCloud Console.

Running llm2sh for the first time will create a template configuration file at ~/.config/llm2sh/llm2sh.json.
You can specify a different path using the -c or –config option.

Before using llm2sh, you need to set up the configuration file with your API keys and preferences.
You can also use the OPENAI_API_KEY, CLAUDE_API_KEY, and GROQ_API_KEY environment variables to specify the
API keys.

To use llm2sh, run the following command followed by your request:

llm2sh [options]

For example:

Basic usage:

$ llm2sh “list all files in the current directory”

You are about to run the following commands:
$ ls -a
Run the above commands? [y/N]

Use a specific model for command generation:

$ llm2sh -m gpt-3.5-turbo “find all Python files in the current directory, recursively”

You are about to run the following commands:
$ find . -type f -name “*.py”
Run the above commands? [y/N]

llm2sh supports running multiple commands in sequence, and supports interactive commands like sudo:

llm2sh “install docker in rootless mode”

You are about to run the following commands:
$ sudo newgrp docker
$ sudo pacman -Sy docker-rootless-extras
$ sudo usermod -aG docker “$USERNAME”
$ dockerd-rootless-setuptool.sh install
Run the above commands? [y/N]

Run the generated command without confirmation:

llm2sh –force “delete all temporary files”

-h, –help show this help message and exit
-c CONFIG, –config CONFIG
specify config file, (Default: ~/.config/llm2sh/llm2sh.json)
-d, –dry-run do not run the generated command
-l, –list-models list available models
-m MODEL, –model MODEL
specify which model to use
-t TEMPERATURE, –temperature TEMPERATURE
use a custom sampling temperature
-v, –verbose print verbose debug information
-f, –yolo, –force run whatever GPT wants, without confirmation

llm2sh currently supports the following LLMs for command generation:

(Ratings are based on my subjective opinion and experience. Your mileage may vary.)

Model Name
Provider
Accuracy
Cost
Notes

local
N/A
¯(ツ)/¯
FREE
Needs local OpenAI API compatible LLM Api Endpoint (i.e. llama.cpp)

groq-llama3-70b
Groq
🧠🧠🧠
FREE (with rate limits)
Blazing fast; recommended

groq-llama3-8b
Groq
🧠🧠
FREE (with rate limits)
Blazing fast

groq-mixtral-8x7b
Groq
🧠
FREE (with rate limits)
Blazing fast

groq-gemma-7b
Groq
🧠
FREE (with rate limits)
Blazing fast

gpt-4o
OpenAI
🧠🧠
💲💲💲
Default model

gpt-4-turbo
OpenAI
🧠🧠🧠
💲💲💲💲

gpt-3.5-turbo-instruct
OpenAI
🧠🧠
💲💲

claude-3-opus
Claude
🧠🧠🧠🧠
💲💲💲💲
Fairly slow (>10s)

claude-3-sonnet
Claude
🧠🧠🧠
💲💲💲
Somewhat slow (~5s)

claude-3-haiku
Claude
🧠
💲💲

✅ Support multiple LLMs for command generation
⬜ User-customizable system prompts
⬜ Integrate with tool calling for more complex commands
⬜ More complex RAG for efficiently providing relevant context to the LLM
⬜ Better support for executing complex interactive commands
⬜ Interactive configuration & setup via the command line

llm2sh does not store any user data or command history, and it does not record or send any telemetry
by itself. However, the LLM APIs may collect and store the requests and responses for their own purposes.

To help LLMs generate better commands, llm2sh may send the following information as part of the LLM
prompt in addition to the user’s request:

Your operating system and version
The current working directory
Your username
Names of files and directories in your current working directory
Names of environment variables available in your shell. (Only the names/keys are sent, not the values).

Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request on the GitHub repository.

This project is licensed under the GPLv3.

llm2sh is an experimental tool that relies on LLMs for generating shell commands. While it can be helpful, it’s important to review and understand the generated commands before executing them, especially when using the YOLO mode. The developers are not responsible for any damages or unintended consequences resulting from the use of this tool.

This project is not affiliated with OpenAI, Claude, or any other LLM provider or creator.
This project is not affiliated with my employer in any way. It is an independent project created for educational and research purposes.

>>> Read full article>>>
Copyright for syndicated content belongs to the linked Source : Hacker News – https://github.com/randombk/llm2sh