Metadata-Version: 2.4
Name: roo-conf
Version: 0.1.13
Summary: A configuration and prompt updater for Roo Code
Author-email: Mark Stouffer <1802850+InTEGr8or@users.noreply.github.com>
Requires-Python: >=3.12
Description-Content-Type: text/markdown

# roo-conf

A Python package to deploy configuration and prompt files for Roo Code into a repository.

## Purpose

This package provides a command-line utility (`roo-conf`) that copies specific configuration and prompt files from either the installed package or a configured remote Git repository to a `.roo` directory within the current working directory of a Git repository. This allows for easy deployment and management of Roo Code configurations across different projects.

## Installation

You can install `roo-conf` using `uv`:

```bash
uv pip install roo-conf
```

## Usage

The `roo-conf` command supports several subcommands: `deploy`, `edit`, `config`, `pull`, `sync-modes`, and `extract-conversations`.

**Note:** While `uvx roo-conf` is the intended way to run installed console scripts, there seems to be a caching issue with `uvx` that prevents it from picking up the latest changes to the package metadata, resulting in an "invalid console script" error. Until this is resolved, it is recommended to use `uv run roo-conf` to execute the package's commands within the project's virtual environment.

### Deploying Prompts (Componentized)

Navigate to the root directory of your Git repository in the terminal. Then, execute the `deploy` subcommand using `uv run`.

You can now deploy specific components of the template by providing their names or glob patterns as arguments. Default system prompts are always included.

```bash
uv run roo-conf deploy [component1] [component2] ...
```

Replace `[component1] [component2] ...` with the names of the components or glob patterns you want to deploy (e.g., `cdk`, `typescript/**/*`).

If no components are specified, all available templates from the configured source will be deployed.

This will create a `.roo` directory in your current repository (if it doesn't exist) and copy the necessary configuration files into it, replacing the `{{repo-full-path}}` placeholder with the absolute path to your repository. If a remote template source is configured and available, it will use templates from there; otherwise, it will fall back to using templates included in the package.

### Editing Source Template Files

To edit a source template file, use the `edit` subcommand followed by the template file name. The file will be opened using your configured editor.

```bash
uv run roo-conf edit <template_name>
```

Replace `<template_name>` with the name of the template file you want to edit (e.g., `system-prompt-code-gh.md`). Note that you should now provide the full file name, including the extension.

The `edit` command will attempt to open the source file from your configured remote template repository first. If a remote source is not configured or the file is not found there, it will indicate that the file is a package resource and cannot be edited directly.

If you run the `edit` subcommand without a filename, it will list the available template files from the configured source (remote if configured and available, otherwise package). When listing from a remote source, it will exclude the `.git` directory and only list markdown files.

```bash
uv run roo-conf edit
```

### Configuring roo-conf

To set configuration options for `roo-conf`, use the `config` subcommand followed by the key and value. You can configure your preferred editor and the remote template source repository.

```bash
uv run roo-conf config editor <editor_command>
```

Replace `<editor_command>` with the command to launch your preferred text editor (e.g., `code`, `nano`, `vim`).

```bash
uv run roo-conf config template_source_repo <repo_url>
```

Replace `<repo_url>` with the URL of the Git repository containing your prompt templates. This setting is stored in a configuration file in your user's home directory (`~/.config/roo-conf/config.json`).

### Pulling Remote Templates

If you have configured a remote template source repository, you can pull the latest templates using the `pull` subcommand. This will clone the repository (if it doesn't exist locally) or pull updates using sparse checkout to only fetch markdown files.

```bash
uv run roo-conf pull
```

### Synchronizing Custom Modes

The `sync-modes` command synchronizes the `custom_modes.yaml` file between your VS Code and VS Code Insiders installations. It finds the latest version of the file based on modification time and copies it to the other location(s).

```bash
uv run roo-conf sync-modes
```

This command is useful for keeping your custom modes consistent across different VS Code installations.

### Extracting Conversations

The `extract-conversations` command extracts conversation history from VS Code's global storage for a specified repository.

```bash
uv run roo-conf extract-conversations [target_repo_path]
```

Replace `[target_repo_path]` with the absolute path to the repository for which you want to extract conversations. If not provided, it defaults to the current working directory. The extracted conversations will be saved as Markdown files in a `.roo-conf/conversations/` subfolder within the target repository.

## Development

### Building Locally

To build the package locally (create the source distribution and wheel), you can use the `./publish.sh` script. This script will:
1. Clear the `uv` cache.
2. Build the source distribution and wheel using `hatch build`.

```bash
./publish.sh
```

### Automated Publishing

Publishing to PyPI is automated via a GitHub Actions workflow. When a new Git tag starting with `v` (e.g., `v1.0.0`) is pushed to the repository, the workflow defined in `.github/workflows/workflow.yml` will trigger. This workflow will build the package and publish it to PyPI.

To publish a new version:
1. Manually update the `version` in `pyproject.toml`.
2. Commit the changes.
3. Create a new Git tag matching the version (e.g., `git tag v1.0.0`).
4. Push the commit and the tag (`git push && git push --tags`).

The GitHub Actions workflow requires a PyPI API token stored as a GitHub Secret named `PYPI_API_TOKEN` to authenticate with PyPI.