Configuring Goose¶
Profiles¶
If you need to customize goose, one way is via editing: ~/.config/goose/profiles.yaml
.
It will look by default something like (and when you run goose session start
without the --profile
flag it will use the default
profile):
default:
provider: open-ai
processor: gpt-4o
accelerator: gpt-4o-mini
moderator: passive
toolkits:
- name: developer
requires: {}
Fields¶
provider¶
Provider of LLM. LLM providers that currently are supported by Goose:
Provider | Required environment variable(s) to access provider |
---|---|
openai | OPENAI_API_KEY |
anthropic | ANTHROPIC_API_KEY |
databricks | DATABRICKS_HOST and DATABRICKS_TOKEN |
processor¶
This is the model used for the main Goose loop and main tools -- it should be be capable of complex, multi-step tasks such as writing code and executing commands. Example: gpt-4o
. You should choose the model based the provider you configured.
accelerator¶
Small model for fast, lightweight tasks. Example: gpt-4o-mini
. You should choose the model based the provider you configured.
moderator¶
Rules designed to control or manage the output of the model. Moderators that currently are supported by Goose:
passive
: does not actively intervene in every responsetruncate
: truncates the first contexts when the contexts exceed the max token size
Example profiles.yaml
files¶
provider as anthropic
¶
default:
provider: anthropic
processor: claude-3-5-sonnet-20241022
accelerator: claude-3-5-sonnet-20241022
provider as databricks
¶
default:
provider: databricks
processor: databricks-meta-llama-3-1-70b-instruct
accelerator: databricks-meta-llama-3-1-70b-instruct
moderator: passive
toolkits:
- name: developer
requires: {}
You can tell it to use another provider for example for Anthropic:
default:
provider: anthropic
processor: claude-3-5-sonnet-20241022
accelerator: claude-3-5-sonnet-20241022
moderator: passive
toolkits:
- name: developer
requires: {}
this will then use the claude-sonnet model, you will need to set the ANTHROPIC_API_KEY
to your anthropic API key.
You can also customize Goose's behavior through toolkits. These are set up automatically for you in the same ~/.config/goose/profiles.yaml
file, but you can include or remove toolkits as you see fit.
For example, Goose's unit-test-gen
command sets up a new profile in this file for you:
unit-test-gen:
provider: openai
processor: gpt-4o
accelerator: gpt-4o-mini
moderator: passive
toolkits:
- name: developer
requires: {}
- name: unit-test-gen
requires: {}
- name: java
requires: {}
Adding a toolkit¶
To make a toolkit available to Goose, add it to your project's pyproject.toml. For example in the Goose pyproject.toml file:
[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
my-new-toolkit = "goose.toolkit.my_toolkits:MyNewToolkit" # this is the path to the class that implements the toolkit
Then to set up a profile that uses it, add something to ~/.config/goose/profiles.yaml
:
my-profile:
provider: openai
processor: gpt-4o
accelerator: gpt-4o-mini
moderator: passive
toolkits: # new toolkit gets added here
- developer
- my-new-toolkit
And now you can run Goose with this new profile to use the new toolkit!
Or, if you're developing a new toolkit and want to test it:
Tuning Goose to your repo¶
Goose ships with the ability to read in the contents of a file named .goosehints
from your repo. If you find yourself repeating the same information across sessions to Goose, this file is the right place to add this information.
This file will be read into the Goose system prompt if it is present in the current working directory.
Check out the guide on using .goosehints for more tips.
Note
.goosehints
follows jinja templating rules in case you want to leverage templating to insert file contents or variables.