york-patched 1.0.2

An example of a python package from pre-existing code

York-Patched automates development gruntwork like PR reviews, bug fixing, security patching, and more using a self-hosted CLI agent and your preferred LLMs. Try the hosted version here.

Key Components

• Steps: Reusable atomic actions like create PR, commit changes or call an LLM.
• Prompt Templates: Customizable LLM prompts optimized for a chore like library updates, code generation, issue analysis or vulnerability remediation.
• Patchflows: LLM-assisted automations such as PR reviews, code fixing, documentation etc. built by combining steps and prompts.

Installation

Using Pip

The following optional dependency groups are available.

• security: Installs semgrep and depscan with pip York-Patched 'patchwork-cli[security]' and is required for AutoFix and DependencyUpgrade patchflows.
• rag: Installs chromadb with pip install 'patchwork-cli[rag]' and is required for the ResolveIssue patchflow.
• notifications: Used by steps sending notifications, e.g. slack messages.
• all: installs everything.
• Not specifying any dependency group (pip install patchwork-cli) will install a core set of dependencies that are sufficient to run the GenerateDocstring and GenerateREADME patchflows.

Using Poetry

If you'd like to build from source using poetry, please see detailed documentation here .

York-Patched CLI

The CLI runs Patchflows, as follows:

patchwork <PatchFlow> <?Arguments>

Where

• Arguments: Allow for overriding default/optional attributes of the Patchflow in the format of key=value. If key does not have any value, it is considered a boolean True flag.

Example

For an GenerateDocstring patchflow which patches vulnerabilities based on a scan using Semgrep:

patchwork GenerateDocstring openai_api_key=<YOUR_OPENAI_API_KEY>  gerrit_username=<GERRIT_USERNAME>  gerrit_http_password=<GERRIT_PASSWORD>

Patchflows

York-Patched comes with predefined patchflows, with more added over time. Sample patchflows include:

• GenerateDocstring: Generate docstrings for methods in your code.
• GenerateREADME: Create a README markdown file for a given folder, to add documentation to your repository.

Prompt Templates

Prompt templates are used by patchflows and passed as queries to LLMs. Templates contain prompts with placeholder variables enclosed by {{}} which are replaced by the data from the steps or inputs on every run.

Below is a sample prompt template:

{
  "id": "diffreview_summary",
    "prompts": [
      {
        "role": "user",
        "content": "Summarize the following code change descriptions in 1 paragraph. {{diffreviews}}"
      }
    ]
}

Each patchflow comes with an optimized default prompt template. But you can specify your own using the prompt_template_file=/path/to/prompt/template/file option.

Contributing

Contributions for new patchflows and steps, or to the core framework are welcome. Please look at open issues for details.

• To create a new patchflow, follow these instructions.
• To create a new step, follow these instructions.

Roadmap

Short Term

• Expand patchflow library and integration options
• Patchflow debugger and validation module
• Bug fixing and performance improvements
• Refactor code and documentation

Long Term

• Support large-scale code embeddings in patchflows
• Support parallelization and branching
• Fine-tuned models that can be self-hosted
• Open-source GUI