llm-grok

Plugin for LLM providing access to Grok models using the xAI API

Installation

Install this plugin in the same environment as LLM:

llm install llm-grok

First, obtain an API key from xAI.

Configure the key using the llm keys set grok command:

llm keys set grok
# Paste your xAI API key here

You can also set it via environment variable:

export XAI_API_KEY="your-api-key-here"

You can now access the Grok model. Run llm models to see it in the list.

To run a prompt through grok-beta:

llm -m grok-beta 'What is the meaning of life, the universe, and everything?'

To start an interactive chat session:

llm chat -m grok-beta

Example chat session:

Chatting with grok-beta
Type 'exit' or 'quit' to exit
Type '!multi' to enter multiple lines, then '!end' to finish
> Tell me a joke about programming

To use a system prompt to give Grok specific instructions:

cat example.py | llm -m grok-beta -s 'explain this code in a humorous way'

The grok-beta model accepts the following options, using -o name value syntax:

-o temperature 0.7: The sampling temperature, between 0 and 1. Higher values like 0.8 increase randomness, while lower values like 0.2 make the output more focused and deterministic.
-o max_tokens 100: Maximum number of tokens to generate in the completion.

Example with options:

llm -m grok-beta -o temperature 0.2 -o max_tokens 50 'Write a haiku about AI'

To set up this plugin locally, first checkout the code. Then create a new virtual environment:

git clone https://github.com/hiepler/llm-grok.git
cd llm-grok
python3 -m venv venv
source venv/bin/activate

Now install the dependencies and test dependencies:

pip install -e '.[test]'

To run the tests:

pytest

List available Grok models:

llm grok models

Check your current configuration:

llm grok config

This plugin uses the xAI API. For more information about the API, see:

Contributions are welcome! Please feel free to submit a Pull Request.

Apache License 2.0