treefeeder 0.0.7

Feed the contents of a folder into your ChatGPT/LLM queries faster

treefeeder

About

treefeeder is a command-line interface (CLI) tool designed to transform a folder of files, such as code files, into a structured string. This string includes both the folder structure (in a Unix tree structure format) and the contents of the files. It's an ideal tool for feeding data into ChatGPT or other large language model (LLM) AI assistants for fine-tuning or query answering.

Installation

To install treefeeder, simply run:

pip install treefeeder

Usage

CLI

You can use treefeeder from the command line by passing the directory path along with optional arguments for customization:

treefeeder <directory_path> [-I ignore_patterns] [-P match_patterns] [-S separator_token]

• <directory_path>: The path to the directory you want to process.
• -I ignore_patterns: Patterns to ignore files or directories.
• -P match_patterns: Patterns to match specific files.
• -S separator_token: The separator token used in output (default is [SEP]).

Python API

treefeeder can also be used within Python. To get a string output of your folder structure and file contents, use:

from treefeeder import get_output

output = get_output(directory_path, ignore_patterns=None, match_patterns=None, separator_token='[SEP]')

Example

treefeeder /path/to/my_project -I *.log -P *.py -S "[SEP]"

This command will process the 'my_project' directory, ignore .log files, match .py files, and use [SEP] as the separator token.

Contributing

Contributions are welcome! Please feel free to submit pull requests, suggest features, or report bugs.

License

treefeeder is open-source and available under MIT License.