Nexus One AI — Installer

Quick Start

git clone <cgit-url>
cd cgit
sudo bash install.sh

Server reboots automatically after NVIDIA drivers install. Phase 2 runs on its own after reboot.

On the custom ISO, Ubuntu autoinstall now pauses on the installer network screen so the operator can choose the final IP address from the VM console before installation continues.

Software-Only / Existing Hardware

Run a feasibility scan before quoting or installing on customer-owned hardware:

bash scripts/cezen-feasibility.sh

The checker reports CPU, RAM, disk, NVIDIA GPU/VRAM, tool readiness, available features, and a recommended Cezen profile. It writes JSON to /opt/cezen/feasibility.json when possible, otherwise ./feasibility.json.

Install on existing hardware without the appliance NVIDIA phase:

sudo bash install.sh --software-only --profile=auto

For small systems or slow customer networks, the installer skips default model downloads on lightweight profiles. To force the same behavior manually:

sudo bash install.sh --software-only --profile=cpu-ai --skip-model-pull

Profiles:

Profile	Use When	Installs
core	no GPU / low RAM	portal, backend, nginx, health/metrics API
cpu-ai	32 GB+ RAM, no usable GPU	core + Chroma/Ollama CPU path, model pull optional
gpu-starter	24-32 GB VRAM	local AI starter stack, model pull optional
gpu-standard	48-96 GB VRAM	standard GPU stack
gpu-pro	multi/high-VRAM GPU	advanced GPU stack
gpu-max	multi-node or HGX-class	full stack, custom sizing

Sellable v1 Admin APIs

The backend exposes the first productization APIs for software-only and appliance deployments:

API	Purpose
GET /api/license	Shows current tier, feature matrix, and whether the tier is locked by Cezen.
GET /api/system/feasibility	Returns the generated hardware feasibility report or live fallback.
GET /api/system/readiness-report	Combines license, feasibility, and install readiness into a customer-facing report payload.
GET /api/audit/report?days=7	Basic audit summary for handover and admin review.
GET /api/system/backups	Lists local backups.
POST /api/system/backups	Creates a local backup of Cezen data.
POST /api/system/backups/{name}/restore	Restores a named local backup and creates a pre-restore safety snapshot.

CLI backup helper:

sudo bash scripts/cezen-backup.sh backup
sudo bash scripts/cezen-backup.sh list
sudo bash scripts/cezen-backup.sh restore /opt/cezen/backups/cezen-backup-YYYYmmdd-HHMMSS.zip

What Gets Installed (Entry Tier)

Service	Port	Notes
Ollama	11434	LLM inference, 2 models pre-loaded
Open WebUI	3001	Chat interface
vLLM	8000	OpenAI-compatible API (start manually)
JupyterLab	8888	Token: cezen2024
ChromaDB	8100	Vector DB for RAG
MLflow	5000	Experiment tracking
MinIO	9001	Object storage (user: cezenadmin / Cezen@2024!)
Grafana	3000	GPU + system monitoring (admin / cezen2024)

Testing Without a GPU (Multipass)

# On your MacBook:
multipass launch 22.04 --name cezen-test --cpus 4 --mem 8G --disk 40G
multipass shell cezen-test

# Inside the VM:
git clone <cgit-url>
sudo bash install.sh

NVIDIA driver install will succeed but nvidia-smi won't show GPUs — that's expected. All other services will run fine.

Pull More Models

bash models/pull-models.sh --tier=starter   # phi3:mini + embeddings
bash models/pull-models.sh --tier=basic     # llama3.1:8b, mistral:7b, codellama
bash models/pull-models.sh --tier=pro       # + llama3.1:70b, mixtral, deepseek-coder
bash models/pull-models.sh --tier=max       # + llama3.1:405b, mixtral:8x22b

File Structure

cgit/
├── install.sh                    ← Entry point
├── ansible/
│   ├── phase1_nvidia.yml         ← Phase 1: drivers (triggers reboot)
│   ├── starter.yml               ← Phase 2: Starter tier (1 GPU, small team)
│   ├── entry.yml                 ← Phase 2: Basic tier (1–2 GPU, department)
│   ├── pro.yml                   ← Phase 2: Pro tier (2+ GPU, multi-team)
│   ├── max.yml                   ← Phase 2: Max tier (4–8 GPU, enterprise)
│   └── roles/
│       ├── base/                 ← OS, Python, Miniconda, LangChain
│       ├── nvidia/               ← Drivers, CUDA 12.4, cuDNN 9
│       ├── docker/               ← Docker CE + NVIDIA Container Toolkit
│       ├── k3s/                  ← Lightweight Kubernetes
│       ├── ollama/               ← Ollama + Open WebUI
│       ├── vllm/                 ← vLLM inference server
│       ├── jupyterlab/           ← JupyterLab notebooks
│       ├── chromadb/             ← Vector database
│       ├── mlflow/               ← Experiment tracking
│       ├── minio/                ← Object storage
│       └── monitoring/           ← Grafana + Prometheus + DCGM
└── models/
    └── pull-models.sh            ← Pull additional models

Change Default Passwords

Before shipping to a customer, update these:

• JupyterLab token: /opt/cezen/.jupyter/jupyter_lab_config.py
• MinIO: /etc/default/minio
• Grafana: environment vars in monitoring role, or via UI after first login
• MLflow: no auth by default (add reverse proxy if needed)