A comprehensive, enterprise-grade AI dashboard integrating multiple AI platforms including OpenAI GPT-4, Google Cloud Vertex AI, Microsoft Azure OpenAI, AWS SageMaker, and Hugging Face models.

• OpenAI: GPT-4 chat, DALL-E 3 image generation
• Google Cloud Vertex AI: Multimodal AI capabilities
• Microsoft Azure OpenAI: Enterprise-grade cloud AI
• AWS SageMaker: ML model training and deployment
• Hugging Face: Text generation, image generation, code completion, sentiment analysis

• JWT-based authentication
• Rate limiting and security headers
• Redis caching for performance
• MongoDB for persistent storage
• Real-time WebSocket collaboration

• Prometheus metrics collection
• Real-time GPU monitoring (NVIDIA)
• AI-powered analytics with TensorFlow.js
• Docker & Kubernetes deployment ready

• Dark mode toggle
• Internationalization support
• Responsive design
• Real-time updates

• Node.js 18+
• MongoDB (optional, for user management)
• Redis (optional, for caching)
• NVIDIA GPU (optional, for GPU monitoring)

1. Clone the repository

   git clone <repository-url>
   cd ai-dashboard

2. Install dependencies

   npm install

3. Set environment variables (create .env file)

   # Required API Keys
   OPENAI_API_KEY=your_openai_key
   HF_API_KEY=your_huggingface_key
   
   # Optional (for full functionality)
   AZURE_OPENAI_API_KEY=your_azure_key
   AZURE_OPENAI_ENDPOINT=your_azure_endpoint
   GOOGLE_CLOUD_PROJECT_ID=your_gcp_project
   AWS_ACCESS_KEY_ID=your_aws_key
   AWS_SECRET_ACCESS_KEY=your_aws_secret
   
   # NVIDIA Cloud Integration (for NGC services)
   NVIDIA_API_KEY=your_nvidia_ngc_api_key
   NVIDIA_ORG_ID=your_nvidia_org_id
   
   # Database & Cache
   MONGODB_URI=mongodb://localhost:27017/dashboard
   REDIS_URL=redis://localhost:6379
   
   # Security
   JWT_SECRET=your_jwt_secret

# Windows PowerShell
.\start-development.ps1

# Linux/macOS
npm run dev

# Windows PowerShell
.\start-production.ps1

# Linux/macOS
./start-production.sh

For advanced production deployments with health checks, backups, and monitoring:

# Windows PowerShell
.\start-production-enhanced.ps1

# Linux/macOS
./start-production-enhanced.sh

Enhanced Production Features:

• ✅ Automatic health checks and startup validation
• ✅ Environment and dependency verification
• ✅ Automatic backups before deployment
• ✅ Port conflict detection and resolution
• ✅ PM2 ecosystem configuration
• ✅ Comprehensive logging and monitoring
• ✅ Old backup cleanup
• ✅ Optional PM2 auto-startup setup

Enhanced Production Options:

# Create backup only
./start-production-enhanced.sh --backup

# Cleanup old backups
./start-production-enhanced.sh --cleanup

# Setup auto-startup on boot
./start-production-enhanced.sh --setup-startup

The application will be available at http://localhost:3000

ai-dashboard/
├── app.js                    # Main Express server
├── package.json              # Dependencies and scripts
├── ecosystem.config.js       # PM2 process configuration
├── start-production.sh       # Standard Linux/macOS production script
├── start-production.ps1      # Standard Windows production script
├── start-production-enhanced.sh    # Enhanced Linux/macOS production script
├── start-production-enhanced.ps1   # Enhanced Windows production script
├── start-development.ps1     # Windows development script
├── Dockerfile                # Docker containerization
├── docker-compose.yml        # Local development with Docker
├── k8s/                      # Kubernetes deployment
│   └── deployment.yaml
├── logs/                     # Application logs directory
├── backups/                  # Automatic backup storage
├── tests/                    # Test suite
│   └── e2e/                  # End-to-end tests
├── .github/workflows/        # CI/CD pipelines
│   └── ci-cd.yml
└── dashboard/                # Frontend assets
    ├── index.html           # Main dashboard
    ├── script.js            # Frontend logic
    ├── nvidia.js            # NVIDIA GPU integration
    ├── collaboration.js     # Real-time collaboration
    └── styles.css           # Styling

• POST /api/auth/register - User registration
• POST /api/auth/login - User login

• POST /api/ai/text-generation - Hugging Face text generation
• POST /api/ai/image-generation - Stable Diffusion image generation
• POST /api/ai/code-completion - Code completion
• POST /api/ai/sentiment-analysis - Sentiment analysis
• POST /api/ai/openai-chat - OpenAI GPT-4 chat
• POST /api/ai/openai-image - OpenAI DALL-E 3 images
• POST /api/ai/google-vertex - Google Cloud Vertex AI
• POST /api/ai/azure-openai-chat - Azure OpenAI
• POST /api/ai/aws-sagemaker - AWS SageMaker
• POST /api/ai/rag-query - RAG-powered queries
• POST /api/ai/fine-tune - Model fine-tuning

• GET /api/nvidia/models - List available NVIDIA NGC models
• POST /api/nvidia/inference - Run inference on NVIDIA cloud models
• GET /api/nvidia/instances - List NVIDIA cloud instances
• POST /api/nvidia/deploy - Deploy models to NVIDIA cloud
• GET /api/nvidia/org - Get NVIDIA organization info

• GET /api/operations - Operations KPIs
• GET /api/banking - Banking metrics
• GET /api/profits - Revenue & Profits Analytics
• GET /api/gpu - Local NVIDIA GPU metrics
• GET /metrics - Prometheus metrics

• POST /api/docker/containers - Docker container management
• POST /api/kubernetes/deploy - Kubernetes deployments

docker-compose up -d

# Build and run
docker build -t ai-dashboard .
docker run -d -p 3000:3000 --env-file .env ai-dashboard

# Deploy to Kubernetes
kubectl apply -f k8s/deployment.yaml

# Check status
kubectl get pods
kubectl get services

• PM2: Process monitoring and management
• Prometheus: Metrics collection at /metrics
• Logs: Available via pm2 logs ai-dashboard

• Helmet.js security headers
• Express rate limiting
• JWT token authentication
• Input validation and sanitization
• CORS protection

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests
5. Submit a pull request

This project is licensed under the MIT License - see the LICENSE file for details.

For support and questions:

• Create an issue in the repository
• Check the logs: pm2 logs ai-dashboard
• Monitor metrics: http://localhost:3000/metrics

Built with ❤️ for the future of AI-powered enterprise applications