🚀 Production-grade AI/ML project with automated deployment
- ✅ Production-Ready: Docker, CI/CD, full test coverage
- ✅ One-Click Deploy:
make docker-runand you're live - ✅ Well-Documented: Quick start, architecture, API docs
- ✅ Modern Stack: Latest best practices and tools
- ✅ Open Source: MIT licensed, contributions welcome
git clone https://github.com/KlementMultiverse/Basic_RAG.git
cd Basic_RAG
make docker-runmake install
make run# Install dependencies
make install
# Run locally
make run
# Run tests
make test
# Deploy with Docker
make docker-run- 🐳 Docker Support: Containerized for easy deployment
- 🧪 Full Test Coverage: Comprehensive test suite
- 📖 Extensive Documentation: Multi-audience docs (students, CTOs, CEOs)
- 🔄 CI/CD Pipeline: Automated testing and deployment
- 🏗️ SOLID Architecture: Clean, maintainable code
- ⚡ Production-Grade: Ready for real-world use
- 🔒 Security-First: No exposed secrets, best practices
- 📦 One-Click Deploy: Makefile automation
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the project
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Klement Gunndu - Automation Expert & AI/ML Engineer
- 🌐 Portfolio: klementmultiverse.github.io
- 💼 LinkedIn: Connect with me
- 📧 Open for opportunities in AI/ML and automation
This project is licensed under the MIT License - see the LICENSE file for details.
- Built with modern DevOps practices
- Automated with CI/CD pipelines
- Tested and production-ready
⭐ If you find this project useful, please consider giving it a star!