Creating a New Toolkit¶
To add a toolkit, in your code (which doesn't necessarily need to be in the Goose package thanks to plugin metadata!), create a class that derives from the Toolkit class.
Example toolkit class¶
Below is an example of a simple toolkit called Demo that derives from the Toolkit class. This toolkit provides an authenticate tool that outputs an authentication code for a user. It also provides system instructions for the model.
import os
import platform
from goose.toolkit.base import Toolkit, tool
class Demo(Toolkit):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
# Provide any additional tools as needed!
# The docstring of the tool provides instructions to the LLM, so they are important to tune
# you do not have to provide any tools, but any function decorated with @tool will be available
@tool
def authenticate(self, user: str):
"""Output an authentication code for this user
Args:
user (str): The username to authenticate for
"""
# notifier supports any rich renderable https://rich.readthedocs.io/en/stable/introduction.html#quick-start
self.notifier.log(f"[bold red]auth: {str(hash(user))}[/]")
# Provide any system instructions for the model
# This can be generated dynamically, and is run at startup time
def system(self) -> str:
print("new")
return f"""**You must preceed your first message by using the authenticate tool for the current user**
```
platform: {platform.system()}
cwd: {os.getcwd()}
user: {os.environ.get('USER')}
```
"""
Exposing the New Toolkit to Goose¶
To make the toolkit available, add it to the pyproject.toml file and then update your profiles.yaml file.
Update the pyproject.toml file¶
If you're adding the new toolkit to Goose or the Goose Plugins repo, simply find the [project.entry-points."goose.toolkit"] section in pyproject.toml and add a line like this:
[project.entry-points."goose.toolkit"]
developer = "goose.toolkit.developer:Developer"
github = "goose.toolkit.github:Github"
# Add a line like this - the key becomes the name used in profiles
demo = "goose.toolkit.demo:Demo"
If you are adding the toolkit to a different package, see the docs for goose-plugins for more information on how to create a plugins repository that can be used by Goose.
Update the profiles.yaml file¶
And then to set up a profile that uses it, add something to ~/.config/goose/profiles.yaml
default:
provider: openai
processor: gpt-4o
accelerator: gpt-4o-mini
moderator: passive
toolkits:
- name: developer
requires: {}
demo-profile:
provider: openai
processor: gpt-4o
accelerator: gpt-4o-mini
moderator: passive
toolkits:
- developer
- demo
And now you can run goose with this new profile to use the new toolkit!
Note
If you're using a plugin from goose-plugins, make sure goose-plugins is installed in your environment. You can install it via pip:
pipx install goose-ai --preinstall goose-plugins