https://github.com/cskwork/folder-organizer
특정 directory 폴더 정리해주는 앱
https://github.com/cskwork/folder-organizer
Last synced: 18 days ago
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특정 directory 폴더 정리해주는 앱
- Host: GitHub
- URL: https://github.com/cskwork/folder-organizer
- Owner: cskwork
- License: mit
- Created: 2024-11-26T15:00:31.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-15T12:48:03.000Z (about 1 year ago)
- Last Synced: 2025-06-15T14:07:24.469Z (about 1 year ago)
- Language: Python
- Size: 144 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Intelligent File Organizer (IFO)
A sophisticated file organization tool that leverages AI to automatically categorize and organize files using the PARA method (Projects, Areas, Resources, Archives). Built with Python and featuring a modern GUI interface.
## Key Features
- 🤖 **AI-Powered Analysis**: Uses Ollama LLM for intelligent content analysis and file categorization
- 📁 **PARA Methodology**: Organizes files according to the PARA system:
- Projects: Active and upcoming work
- Areas: Ongoing responsibilities
- Resources: Reference materials and tools
- Archives: Completed or inactive items
- 🎨 **Modern GUI Interface**: Built with CustomTkinter for a clean, modern look
- 🌏 **Multilingual Support**: Full support for English and Korean interfaces
- 📊 **Rich File Analysis**:
- Comprehensive metadata extraction
- Content-based categorization
- File type detection
- Document analysis (PDF, Office files, emails, images)
- ⚙️ **Advanced Features**:
- Undo/Redo operations
- Preview organization before applying
- Progress tracking
- Batch processing
- Empty folder cleanup
- Automatic backups
## System Requirements
- Python 3.10 or higher
- Windows 10/11
- 8GB RAM recommended
- [Ollama](https://ollama.ai/) installed and running locally
## Installation
1. Clone the repository:
```bash
git clone https://github.com/yourusername/intelligent-file-organizer.git
cd intelligent-file-organizer
```
2. Create and activate a virtual environment:
```bash
# Windows
python -m venv venv
venv\Scripts\activate
# Linux/macOS
python -m venv venv
source venv/bin/activate
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Install and start Ollama:
- Download from [ollama.ai](https://ollama.ai)
- Install the required model:
```bash
ollama pull mistral
```
## Quick Start
1. Run the application:
```bash
# Windows
run.bat
# Linux/macOS
./run.sh
```
2. Using the interface:
- Select your source directory
- Choose organization options:
- Content Analysis: Uses AI to analyze file contents
- File Type Organization: Groups by file types
- Date Organization: Organizes by creation/modification date
- Remove Empty Folders: Cleans up empty directories
- Click "Analyze" to scan files
- Use "Preview" to see the proposed organization
- Click "Organize" to execute the organization
## Configuration
Edit `config.json` to customize:
- Language settings (english/korean)
- AI model configuration
- File size limits
- Backup preferences
- PARA category names and paths
- Supported file extensions
- Organization rules and thresholds
## File Type Support
- Documents: .txt, .doc, .docx, .pdf, .rtf, .odt, .md, .csv, .json, .xml
- Images: .jpg, .jpeg, .png, .gif, .bmp, .tiff, .webp, .svg
- Videos: .mp4, .avi, .mov, .wmv, .flv, .mkv, .webm
- Audio: .mp3, .wav, .ogg, .m4a, .flac, .aac
- Archives: .zip, .rar, .7z, .tar, .gz, .bz2
- Code: .py, .js, .html, .css, .java, .cpp, .h, .cs, .php
- Data: .xlsx, .xls, .db, .sqlite, .sql
## Error Handling
The application includes comprehensive error handling:
- Automatic retries for failed operations
- Detailed error logging
- User-friendly error messages
- Operation rollback capability
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Acknowledgments
- [CustomTkinter](https://github.com/TomSchimansky/CustomTkinter) for the modern GUI framework
- [Ollama](https://ollama.ai/) for the AI model integration
- The PARA method by Tiago Forte