AI-powered developer onboarding platform that transforms weeks of traditional onboarding into hours of focused learning.
RampForgeAI/
├── frontend/ # NextJS frontend application
├── backend/ # FastAPI backend application
├── docker-compose.yml # Docker development environment
└── README.md # This file
- Node.js 18+
- Python 3.11+
- Docker and Docker Compose (recommended)
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Clone the repository
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Start all services:
docker-compose up --build
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Access the applications:
- Frontend: http://localhost:3000
- Backend API: http://localhost:8000
- API Documentation: http://localhost:8000/api/docs
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Navigate to backend directory:
cd backend -
Create virtual environment:
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
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Install dependencies:
pip install -r requirements.txt
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Copy environment file:
cp .env.example .env
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Start the backend:
cd app python main.py
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Navigate to frontend directory:
cd frontend -
Install dependencies:
npm install
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Start the development server:
npm run dev
- ✅ NextJS project with TypeScript and Tailwind CSS
- ✅ FastAPI backend with proper project structure
- ✅ Docker development environment
- ✅ Health check endpoints
- ✅ Frontend-backend connectivity verification
- Colors: Deep purple (#6750A4), Light lavender (#F2EFF7), Teal (#50A482)
- Typography: Space Grotesk (headlines), Inter (body), Source Code Pro (code)
- Framework: Tailwind CSS with custom configuration
GET /- Root endpointGET /api/health- Health checkGET /api/v1/status- Detailed API statusGET /api/docs- Interactive API documentation
See backend/.env.example for all available configuration options.
The project is ready for implementing the next tasks:
- Authentication and user management system
- Core UI layout and navigation components
- MCP client infrastructure
- AI integration services
Run the setup test script to verify all components are working:
chmod +x test-setup.sh
./test-setup.sh