Contributing#

To contribute to this tool, first checkout the code. Then create a new virtual environment:

cd llm
python -m venv venv
source venv/bin/activate

Or if you are using pipenv:

pipenv shell

Now install the dependencies and test dependencies:

pip install -e '.[test]'

To run the tests:

pytest

Debugging tricks#

The default OpenAI plugin has a debugging mechanism for showing the exact requests and responses that were sent to the OpenAI API.

Set the LLM_OPENAI_SHOW_RESPONSES environment variable like this:

LLM_OPENAI_SHOW_RESPONSES=1 llm -m chatgpt 'three word slogan for an an otter-run bakery'

This will output details of the API requests and responses to the console.

Use --no-stream to see a more readable version of the body that avoids streaming the response:

LLM_OPENAI_SHOW_RESPONSES=1 llm -m chatgpt --no-stream \
  'three word slogan for an an otter-run bakery'

Documentation for this project uses MyST - it is written in Markdown and rendered using Sphinx.

To build the documentation locally, run the following:

cd docs
pip install -r requirements.txt
make livehtml

This will start a live preview server, using sphinx-autobuild.

The CLI --help examples in the documentation are managed using Cog. Update those files like this:

just cog

You’ll need Just installed to run this command.

To release a new version:

Update docs/changelog.md with the new changes.
Update the version number in setup.py
Create a GitHub release for the new version.
Wait for the package to push to PyPI and then…
Run the regenerate.yaml workflow to update the Homebrew tap to the latest version.