NoteSnap / CHANGELOG.md
Prateek-044's picture
Upload 24 files
e9cd410 verified
|
Raw
History Blame Contribute Delete
4.46 kB
# Changelog
All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [Unreleased]
### Added
- Initial project setup and documentation
## [1.0.0] - 2025-01-17
### Added
- πŸ“ **Core Features**
- PDF file upload and text extraction using PyPDF2
- Direct text input for summarization
- AI-powered summarization using Hugging Face Transformers (BART, T5, DistilBART)
- Bullet-point formatted summary output
- Real-time progress indicators during processing
- 🎨 **User Interface**
- Clean Streamlit web interface
- Tabbed layout for PDF upload and text input
- Model selection dropdown (BART, T5, DistilBART)
- Summary length customization (Short, Medium, Long)
- Statistics display (word count, compression ratio)
- Download functionality for generated summaries
- 🐳 **Docker Support**
- Multi-stage Dockerfile for optimized builds
- Docker Compose configuration for easy deployment
- Development Docker setup with live reload
- Production-optimized Docker configuration
- Comprehensive Docker documentation
- πŸ› οΈ **Development Tools**
- Modular code architecture with separate modules
- Comprehensive error handling and user feedback
- Basic testing framework
- Docker build and run scripts
- Development environment setup
- πŸ“š **Documentation**
- Detailed README with installation and usage instructions
- Docker deployment guide
- Troubleshooting section
- API documentation for modules
- πŸ”’ **Security & Performance**
- Non-root Docker container execution
- Input validation and file size limits
- Model caching for improved performance
- Resource limits and health checks
### Technical Details
- **Backend**: Python 3.8+, Streamlit, Hugging Face Transformers, PyTorch
- **AI Models**: BART (facebook/bart-large-cnn), T5, DistilBART
- **PDF Processing**: PyPDF2 with comprehensive error handling
- **Containerization**: Docker with multi-stage builds
- **Architecture**: Modular design with separate PDF processing and summarization modules
### Dependencies
- streamlit>=1.28.0
- transformers>=4.35.0
- torch>=2.0.0
- PyPDF2>=3.0.1
- Additional utilities for text processing and acceleration
---
## Release Notes
### Version 1.0.0 Highlights
πŸŽ‰ **Initial Release** - NoteSnap is now available!
This first release provides a complete solution for document summarization with:
- **Easy-to-use web interface** built with Streamlit
- **Multiple AI models** for different use cases and performance needs
- **Docker support** for consistent deployment across environments
- **Comprehensive documentation** for users and developers
### Supported Platforms
- **Local Installation**: Windows, macOS, Linux with Python 3.8+
- **Docker**: Any platform supporting Docker containers
- **Cloud Deployment**: Compatible with cloud platforms supporting Docker
### Known Limitations
- PDF processing limited to text-based documents (no OCR for scanned images)
- Maximum file size limit of 10MB for PDF uploads
- Internet connection required for initial model downloads
- GPU acceleration optional but recommended for better performance
### Upcoming Features (Roadmap)
- πŸ“± Mobile-responsive interface improvements
- πŸ” OCR support for scanned PDF documents
- 🌐 Multi-language summarization support
- πŸ“Š Advanced analytics and summary quality metrics
- πŸ”— API endpoints for programmatic access
- πŸ“± Progressive Web App (PWA) capabilities
---
## Migration Guide
### From Development to Production
When deploying to production:
1. **Use Docker Compose**:
```bash
docker-compose up -d
```
2. **Configure Environment Variables**:
- Copy `.env.example` to `.env`
- Adjust settings for your environment
3. **Set Resource Limits**:
- Ensure adequate memory (4GB+ recommended)
- Configure CPU limits based on expected load
### Updating Dependencies
To update to newer versions:
```bash
# Update Python packages
pip install -r requirements.txt --upgrade
# Rebuild Docker image
docker-compose build --no-cache
```
---
## Support
For questions, issues, or contributions:
- πŸ› [Report Issues](https://github.com/PRATEEK-260/NoteSnap/issues)
- πŸ’¬ [Discussions](https://github.com/PRATEEK-260/NoteSnap/discussions)
---
**Thank you for using NoteSnap!** πŸŽ‰