shell_gpt
Enrichment pendingA command-line productivity tool powered by AI large language models like GPT-5, will help you accomplish your tasks faster and more efficiently.
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Install
pip install shell_gpt PyPISimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A command-line productivity tool powered by AI large language models like GPT-5, will help you accomplish your tasks faster and more efficiently.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Jul 15, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Jul 15, 2026
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Jul 15, 2026
- Languages
- python
Source: github.language+pyproject.toml · Jul 15, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 15, 2026)
ompted for your key which will then be stored in `~/.config/shell_gpt/.sgptrc`. OpenAI API is not free of charge, please refer to the [OpenAI pricing](https://openai.com/Source link
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README
Installation
pip install shell-gpt
By default, ShellGPT uses OpenAI's API and GPT-4 model. You'll need an API key, you can generate one here. You will be prompted for your key which will then be stored in ~/.config/shell_gpt/.sgptrc. OpenAI API is not free of charge, please refer to the OpenAI pricing for more information.
[!TIP] Alternatively, you can run open-source models locally for free. This requires setting up your own LLM backend, such as Ollama. To get ShellGPT working with Ollama, follow this detailed guide
❗️Note that ShellGPT is not optimized for local models and may not work as expected.
-> docker run -d -p 80:80 -v $(pwd)/index.html:/usr/share/nginx/html/index.html nginx
-> It appears that jq is not installed on the system. Let me try to install it using brew.
-> @FunctionCall execute_shell_command(shell_command="brew install jq")
Docker
Run the container using the OPENAI_API_KEY environment variable, and a docker volume to store cache. Consider to set the environment variables OS_NAME and SHELL_NAME according to your preferences.
docker run --rm \
--env OPENAI_API_KEY=api_key \
--env OS_NAME=$(uname -s) \
--env SHELL_NAME=$(echo $SHELL) \
--volume gpt-cache:/tmp/shell_gpt \
ghcr.io/ther1d/shell_gpt -s "update my system"
Example of a conversation, using an alias and the OPENAI_API_KEY environment variable:
alias sgpt="docker run --rm --volume gpt-cache:/tmp/shell_gpt --env OPENAI_API_KEY --env OS_NAME=$(uname -s) --env SHELL_NAME=$(echo $SHELL) ghcr.io/ther1d/shell_gpt"
export OPENAI_API_KEY="your OPENAI API key"
sgpt --chat rainbow "what are the colors of a rainbow"
sgpt --chat rainbow "inverse the list of your last answer"
sgpt --chat rainbow "translate your last answer in french"
You also can use the provided Dockerfile to build your own image:
docker build -t sgpt .
For agents
This page has a .md twin and JSON over the API.