Metadata-Version: 2.4
Name: shawtie
Version: 1.0.1
Summary: AI-powered file organization tool for Linux
Home-page: https://github.com/Turbash/shawtie
Author: Turbash Negi
Author-email: negirawatdeepi@gmail.com
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: End Users/Desktop
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Operating System :: POSIX :: Linux
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: requests>=2.28.0
Requires-Dist: pydub>=0.25.0
Requires-Dist: rich>=13.0.0
Requires-Dist: Pillow>=9.0.0
Requires-Dist: mutagen>=1.45.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# Shawtie

## File Sorting Framework

Shawtie is an AI powered file organization tool that uses ai to analyse, rename, and categorizes your files into structured folders. It uses ai to understand file content and generate descriptive names, making messy directories clean and searchable. Built for Linux, it handles images, documents, videos, audio files, and more.

- AI Smart Renaming

- Auto Caegorization into folders

- Recursive Sorting inside folders

- Metadata Viewer

- History tracking 

- Undo Function

- Dolphin integration to use actions with right - click.

- Beautiful progress bars and colourful ooutpts.

- Can see a dry run of what changes will be done.

## Demo

Demo video will be here

## How to run locally

1. Clone the repository

```
git clone https://github.com/Turbash/shawtie
cd shawtie
```

2. Install the dependencies

```
pip install -r requirements.txt
```

3. Run the main file with target folder (there are other ways to run also watch demo)

```
python main.py test_files
```

## Requirements

A decent version of python and pip

KDE Dolphin if you want to test dolphin integration.

## pip package

You can now use shawtie simply by installing it with this command:

```
pip install shawtie
```

The package can be seen on https://pypi.org/project/shawtie/
