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.gitignore

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agentaflow-sro-community.code-workspace
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docs/screenshots/README.md
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docker/PHASE1-COMPLETE.md
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docs/DOCUMENTATION-UPDATE-SUMMARY.md

README.md

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> **Demo Ready**: All screenshots show the dashboard running on a local laptop without requiring NVIDIA hardware - perfect for demonstrations and development!
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## �📦 Installation
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## 📦 Installation
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### Option 1: Docker (Recommended - Fastest Setup)
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```bash
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# Run web dashboard with Docker
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docker run -p 9000:9000 -p 9001:9001 ghcr.io/finoptimize/agentaflow-sro-community:web-dashboard
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# Or use Docker Compose for complete stack (Dashboard + Prometheus + Grafana)
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curl -O https://raw.githubusercontent.com/Finoptimize/agentaflow-sro-community/main/docker-compose.yml
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docker-compose up -d
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# Access at:
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# - Dashboard: http://localhost:9000
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# - Grafana: http://localhost:3000 (admin/agentaflow123)
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# - Prometheus: http://localhost:9090
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```
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### Option 2: From Source
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```bash
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go get github.com/Finoptimize/agentaflow-sro-community
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```
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## 🎯 Quick Start
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### With Docker (30 seconds)
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```bash
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# Single command - web dashboard with real-time GPU monitoring
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docker run -p 9000:9000 -p 9001:9001 agentaflow-sro:web-dashboard
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# Or complete monitoring stack
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docker-compose up -d
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```
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### From Source (5-10 minutes)
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Run the comprehensive demo:
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```bash
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This demonstrates all three core components working together.
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### Build Docker Images Locally
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```bash
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# Build web dashboard
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docker build -f docker/Dockerfile.web-dashboard -t agentaflow-sro:web-dashboard .
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# Build all images
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./docker/build.ps1 # Windows
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./docker/build.sh # Linux/Mac
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# See docker/README.md for complete documentation
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```
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## 💡 Usage Examples
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### GPU Scheduling
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├── cmd/
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│ ├── agentaflow/ # Main CLI application
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│ └── k8s-gpu-scheduler/ # Kubernetes GPU scheduler
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├── docker/
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│ ├── Dockerfile.web-dashboard # Web dashboard container (15-20MB)
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│ ├── Dockerfile.k8s-scheduler # Kubernetes scheduler container
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│ ├── Dockerfile.prometheus-demo # Prometheus demo container
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│ └── README.md # Docker documentation
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├── docker-compose.yml # Complete stack orchestration
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├── monitoring/
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│ ├── prometheus.yml # Prometheus configuration
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│ └── prometheus/rules/ # Alert rules
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└── examples/
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├── k8s/ # Kubernetes deployment examples
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├── monitoring/ # Grafana dashboards and configs
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└── demo/ # Demo applications
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```
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## 🐳 Container Deployment
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AgentaFlow is fully containerized for instant deployment:
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### Production-Ready Docker Images
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All images are security-hardened with:
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- **Distroless base** (no shell, minimal attack surface)
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- **15-20MB size** (98% smaller than typical Go images)
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- **Non-root execution** (UID 65532)
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- **Built-in health checks**
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- **Multi-architecture** support (AMD64 + ARM64)
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### Available Images
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| Image | Size | Purpose | Ports |
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|-------|------|---------|-------|
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| `web-dashboard` | ~20MB | Real-time GPU monitoring UI | 9000, 9001 |
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| `k8s-scheduler` | ~20MB | Kubernetes GPU scheduler | 8080 |
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| `prometheus-demo` | ~20MB | Metrics integration demo | 8080 |
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### Docker Compose Stack
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The complete monitoring stack includes:
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- AgentaFlow Web Dashboard
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- Prometheus (metrics collection)
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- Grafana (visualization)
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- Pre-configured dashboards and alerts
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For detailed Docker documentation, see [docker/README.md](docker/README.md) and [CONTAINER.md](CONTAINER.md)
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## � Taking Screenshots
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To add actual screenshots to this README:
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## 🛠️ Requirements
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### With Docker (Recommended)
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- Docker Desktop or Docker Engine 20.10+
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- Docker Compose 2.0+ (for full stack)
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- 2GB RAM minimum, 4GB recommended
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- No Go installation required!
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### From Source
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- Go 1.21 or higher
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- No external dependencies for core functionality
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- Kubernetes 1.20+ (for Kubernetes GPU scheduling features)
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- NVIDIA GPU drivers and nvidia-docker (for GPU monitoring)
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- NVIDIA GPU drivers and nvidia-docker (optional, for real GPU monitoring)
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## 📝 License
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-**Production-ready observability** - Enterprise-grade metrics export and visualization
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-**Web dashboard for monitoring** - Interactive real-time web interface with charts and alerts
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-**OpenTelemetry distributed tracing** - Complete tracing integration with Jaeger/OTLP support
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-**Docker containerization** - Production-ready containers with Docker Compose orchestration
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- 🚧 **CI/CD with GitHub Actions** - Automated builds and publishing to GitHub Packages (In Progress)
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- 📋 **Multi-architecture builds** - AMD64 + ARM64 container support (Planned)
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- 📋 **Helm charts** - Kubernetes deployment templates (Planned)
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## 🚀 Enterprise Edition (Coming Soon)
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