We welcome Pull Requests for general contributions. If you have a larger new feature or any questions on how to develop a fix, we recommend you open an issue before starting.
Goose uses uv for dependency management, and formats with ruff.
Clone goose and make sure you have installed uv
to get started. When you use
uv
below in your local goose directly, it will automatically setup the virtualenv
and install dependencies.
We provide a shortcut to standard commands using just in our justfile
.
Now that you have a local environment, you can make edits and run our tests!
If you've made edits and want to try them out, use
uv run goose session start
or other goose
commands.
If you want to run your local changes but in another directory, you can use the path in the virtualenv created by uv:
alias goosedev=`uv run which goose`
You can then run goosedev
from another dir and it will use your current changes.
To run the test suite against your edges, use pytest
:
uv run pytest tests -m "not integration"
or, as a shortcut,
just test
Enable traces in Goose with locally hosted Langfuse
Note
This integration is experimental and we don't currently have integration tests for it.
Developers can use locally hosted Langfuse tracing by applying the custom observe_wrapper
decorator defined in packages/exchange/src/langfuse_wrapper.py
to functions for automatic integration with Langfuse.
- Run
just langfuse-server
to start your local Langfuse server. It requires Docker. - Go to http://localhost:3000 and log in with the default email/password output by the shell script (values can also be found in the
.env.langfuse.local
file). - Run Goose with the --tracing flag enabled i.e.,
goose session start --tracing
- View your traces at http://localhost:3000
To extend tracing to additional functions, import from exchange.langfuse_wrapper import observe_wrapper
and use the observe_wrapper()
decorator on functions you wish to enable tracing for. observe_wrapper
functions the same way as Langfuse's observe decorator.
Read more about Langfuse's decorator-based tracing here.
The lower level generation behind goose is powered by the exchange
package, also in this repo.
Thanks to uv
workspaces, any changes you make to exchange
will be reflected in using your local goose. To run tests
for exchange, head to packages/exchange
and run tests just like above
uv run pytest tests -m "not integration"
Given that so much of Goose involves interactions with LLMs, our unit tests only go so far to confirming things work as intended.
We're currently developing a suite of evaluations, to make it easier to make improvements to Goose more confidently.
In the meantime, we typically incubate any new additions that change the behavior of the Goose through opt-in plugins - Toolkit
s, Moderator
s, and Provider
s. We welcome contributions of plugins that add new capabilities to goose. We recommend sending in several examples of the new capabilities in action with your pull request.
Additions to the developer toolkit change the core performance, and so will need to be measured carefully.
This project follows the Conventional Commits specification for PR titles. Conventional Commits make it easier to understand the history of a project and facilitate automation around versioning and changelog generation.
In order to release a new version of goose, you need to do the following:
- Update CHANGELOG.md. To get the commit messages since last release, run:
just release-notes
- Update version in
pyproject.toml
forgoose
and package dependencies such asexchange
- Create a PR and merge it into main branch
- Tag the HEAD commit in main branch. To do this, switch to main branch and run:
just tag-push
- Publish a new release from the Github Release UI