CosmoLens AI is a full-stack Space Intelligence System that combines machine learning, backend APIs, and interactive 3D visualization to explore and analyze astronomical objects.
The system is built using a modular architecture to clearly separate frontend, backend, and ML responsibilities.
CosmoLens AI consists of two primary modules:
- Explore galaxies, nebulae, and celestial objects
- Interactive 3D visualization
- AI-powered object insights
- Timeline and research notes
- Predict planetary habitability using machine learning
- Multi-class classification:
- Non-Habitable
- Potentially Habitable
- Habitable
- Probability distribution output
- Feature importance ranking
- Physics-informed feature engineering
The project follows a modular full-stack architecture:
Frontend → Backend API → ML Inference → Trained Model
Each layer is isolated and independently maintainable.
cosmolens-ai/ │ ├── frontend/ → Web UI (React / Next.js) ├── backend/ → API Layer (Routes, Services, Validators) ├── ml/ → ML Pipeline (Training & Inference) ├── docs/ → Architecture & API documentation ├── project_plan.md └── README.md
Each member works only in their assigned module:
- Frontend Developers →
/frontend - Backend Developers →
/backend - ML Engineer →
/ml - Team Lead → Architecture review & GitHub management
Do NOT modify folders outside your responsibility without discussion.
- Pull latest changes
- Work in your assigned folder
- Create feature branch
- Commit with clear messages
- Push branch
- Open Pull Request
- Team Lead reviews & merges
Run these commands from the repository root:
npm install --prefix frontend
npm run devnpm run dev starts the frontend, backend, and Firebase emulators together and stops all of them together on Linux, macOS, and Windows.
Useful variants:
npm run dev:appstarts only the frontend appnpm run dev:web-onlystarts only the frontend app without the local stack wrapper
Backend setup still requires the Python virtual environment in /.venv with backend/requirements.txt installed.
- This is a private development repository.
- Do not share outside the team.
- Do not commit large datasets or temporary files.
- Keep commits structured and meaningful.
We are transitioning from API-based logic to a true ML-driven planetary prediction system with proper model training and evaluation.
Maintained by Team CosmoLens AI.