A Django-based catalog for managing and evaluating AI packages and tools in the Rockae ecosystem. The platform helps teams discover, compare, and track the performance of AI-related packages.
- AI Package Management: Catalog and organize AI packages with detailed metadata
- Categorization: Classify packages by AI functionality (NLP, Computer Vision, Generation, etc.)
- Integration Types: Support for various integration methods (API, Library, Plugin)
- Performance Tracking: Store and monitor performance metrics for each package
- Popularity Metrics: Track package adoption and usage statistics
- Model Compatibility: Document supported AI models and versions
- Python 3.x
- Django
- Database (SQLite by default, configurable)
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Clone the repository:
git clone <repository-url> cd Software.Architecture.Packages
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Install dependencies:
pip install -r requirements.txt
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Run migrations:
python manage.py migrate
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Start the development server:
python manage.py runserver
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Verify your setup:
python -c "import django; print(django.get_version())"
Software.Architecture.Packages/
├── README.md # Project overview and setup guide
├── models.py # Core package catalog models
├── LICENSE # MIT license text
└── .gitignore # Ignored files and local artifacts
The core RockaePackageCatalogue model includes:
name: Package/tool namedescription: Detailed functionality descriptionrepository_url: Source code repository linkai_category: AI functionality categoryintegration_type: Integration methodsupported_models: Compatible AI modelspopularity_score: Usage popularity metricperformance_metrics: Benchmarks and metrics data
The system provides RESTful APIs for package management:
- GET
/api/packages/: List all packages - POST
/api/packages/: Register new package - GET
/api/packages/<id>/: Get package details - PUT
/api/packages/<id>/: Update package - DELETE
/api/packages/<id>/: Remove package
- Fork the repository
- Create a feature branch
- Commit your changes
- Push to the branch
- Create a Pull Request
This project is licensed under the terms specified in the MIT LICENSE file.
For support or questions, please open an issue in this repository and include reproduction details when possible.