Quick Start

Prerequisites

Docker Desktop (includes Docker Compose)
GNU Make (pre-installed on most Linux/macOS systems; on Windows use WSL or install via choco install make)
Git

No Python, Node.js, or database installs required — everything runs in containers.

Install

git clone https://github.com/arialabs/nova.git
cd nova
./setup

The setup wizard handles the rest.

What the setup wizard does

Copies .env.example to .env if it doesn’t exist
Detects GPU availability (NVIDIA / AMD ROCm)
Asks about your deployment mode (cloud-only, local model serving, remote GPU)
Configures LLM provider API keys
Pulls selected Ollama models (if using local inference)
Starts all services via Docker Compose

When it finishes, open http://localhost:3001 to access the dashboard.

Remote GPU (optional)

If you have a separate machine with a GPU for AI inference:

# Run this ON the GPU machine:
bash <(curl -s https://raw.githubusercontent.com/arialabs/nova/main/scripts/setup-remote-ollama.sh)

Then re-run ./setup on the Nova machine and choose “Remote GPU”. The wizard will ask for the GPU machine’s IP address and configure Wake-on-LAN if desired.

Manual configuration

If you prefer to skip the wizard:

cp .env.example .env
# Edit .env with your preferred settings
make dev

See Configuration for all available settings.

Verify everything is running

Check container status:

make ps

All 7 core services should show as healthy. Hit the health endpoints to confirm:

Service	Health endpoint
orchestrator	`http://localhost:8000/health/live`
llm-gateway	`http://localhost:8001/health/live`
memory-service	`http://localhost:8002/health/live`
chat-api	`http://localhost:8080/health/live`
dashboard	`http://localhost:3001`
recovery	`http://localhost:8888/health/live`

You can also test the chat interface at http://localhost:8080/ for an interactive demo.

Next steps

Architecture — understand how the services fit together
Configuration — configure providers, models, and routing
Deployment — production commands, GPU overlays, backups