Utility to apply changes to files in a directory based on AI-generated recommendations from prepdir.
Project description
applydir
A utility to apply changes to a codebase based on AI-generated recommendations from a prepped_dir.txt file (generated by prepdir). Designed for vibe coding with UI-based LLMs like Grok 3, enabling seamless integration of AI-suggested changes.
Installation
pip install applydir
Usage
-
Generate a
prepped_dir.txtfile usingprepdir:prepdir . -
Modify
prepped_dir.txt(or create amodified_prepped_dir.txt) with your AI assistant, including updated file contents and additional commands. -
Apply changes using
applydir:applydir modified_prepped_dir.txt --base-dir /path/to/codebase
-
Use
--dry-runto preview changes without applying them:applydir modified_prepped_dir.txt --base-dir /path/to/codebase --dry-run
-
Specify a custom config file:
applydir modified_prepped_dir.txt --base-dir /path/to/codebase --config custom_config.yaml
-
Configuration
The config.yaml file (default: src/applydir/config.yaml) allows customization:
apply_changes:
auto_apply: false # Set to true to apply changes without user confirmation
commands:
shell_type: "bash" # Options: "bash", "powershell", "cmd"
logging:
level: "INFO" # Options: "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"
auto_apply: Iftrue, applies file changes automatically without prompting.shell_type: Specifies the shell for additional commands (commands are not executed automatically).logging.level: Controls verbosity of logs.
Features
- Parses
prepped_dir.txtto extract file contents and additional commands. - Compares original and modified files, showing diffs for updates.
- Supports creating new files and updating existing ones.
- Configurable via
config.yamlfor automatic application and shell type. - Dry-run mode to preview changes.
- Logging for better debugging and transparency.
Development
To set up the development environment:
git clone https://github.com/eyecantell/applydir
cd applydir
pdm install
pdm install -G test
Run tests:
pdm run pytest
Contributing
Contributions are welcome! Please open an issue or submit a pull request at https://github.com/eyecantell/applydir.
License
MIT License
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