Getting started with Patchwork in 5 minutes
pip install 'patchwork-cli[security]'
and is required for AutoFix and DependencyUpgrade patchflows.pip install 'patchwork-cli[rag]'
and is required for the ResolveIssue patchflow.pip install patchwork-cli
) will install a core set of dependencies that are sufficient to run the GenerateDocstring, PRReview and GenerateREADME patchflows.key=value
. If key
does not have any value, it is considered a boolean True
flag.default.yml
file for the list of configurations you can set to manage the AutoFix patchflow. For more details on how you can use a personal access token from GitHub on CLI you can read this.
You will need to pass your own openai_api_key
to call the LLM. Otherwise, to get started, you can get a patched_api_key
for free by
by signing in at https://app.patched.codes/signin and generating an API key from the integrations tab. You can then call the patchflow with the key as follows:
google_api_key
and model
, this is useful if you want to work with large contexts as the gemini-pro-1.5
model supports a input context length of 1 million tokens.
The patchwork-configs repository contains the default configuration and prompts for all the patchflows. You can clone that repo and pass it as a flag to the CLI: