Ask GPT to run a command
Project description
llm2sh
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.
Features
- 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
Installation
pip install llm2sh
Usage
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.
Configuration
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.
Basic Usage
To use llm2sh
, run the following command followed by your request:
llm2sh [options] <request>
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 likesudo
:
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"
Options
-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
Supported Models
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) |
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 | 🧠 | 💲💲 | |
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 |
Roadmap
- ✅ 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
Privacy
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).
Contributing
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.
License
This project is licensed under the GPLv3.
Disclaimer
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.
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