Skynet-config/guida_ai_server_supermicro.md

# Supermicro X9DRW-iF AI Coding Server
## Guida Completa Setup Produzione CPU-Only

## Hardware

### Server
- Supermicro X9DRW-iF
- 2x Intel Xeon E5-2680 v2
- 256GB ECC DDR3

### Storage
- SSD SATA 128GB
- HDD WD Red 2TB

### Obiettivo
Server AI locale per:
- coding assistant
- repository analysis
- RAG
- AI agent
- inferenza locale CPU-only
- accesso web LAN

---

# Architettura Finale

## SSD 128GB
Sistema operativo + runtime AI

Contiene:
- Debian
- Ollama
- Open WebUI
- cache runtime
- modello attivo

---

## HDD 2TB
Storage AI

Contiene:
- modelli GGUF
- repository Git
- vector database
- dataset
- backup

---

# 1. Installazione Debian

## ISO consigliata

Debian 12 minimal netinstall

Sito:
https://www.debian.org/download

---

## Durante installazione

### Selezionare:
- SSH Server
- Standard system utilities

### NON selezionare:
- Desktop Environment
- GNOME
- KDE
- print server
- web server

---

# 2. Configurazione dischi

## SSD 128GB

### Partizionamento

| Mount | Size |
|---|---|
| / | 100GB |
| swap | 8-16GB |

Filesystem:
- ext4

---

## HDD 2TB

Filesystem:
- ext4

Mount point:

```bash
/mnt/ai-data
```

---

# 3. Primo avvio

Aggiornare sistema:

```bash
sudo apt update && sudo apt upgrade -y
```

Installare utility:

```bash
sudo apt install -y \
git curl wget htop btop tmux nano \
build-essential cmake python3 python3-pip \
nvme-cli unzip
```

---

# 4. Configurazione HDD

## Identificare UUID

```bash
sudo blkid
```

## Creare mountpoint

```bash
sudo mkdir -p /mnt/ai-data
```

## Modificare fstab

```bash
sudo nano /etc/fstab
```

Aggiungere:

```fstab
UUID=INSERISCI_UUID /mnt/ai-data ext4 defaults,noatime 0 2
```

## Test mount

```bash
sudo mount -a
```

Verifica:

```bash
df -h
```

---

# 5. Ottimizzazioni CPU

## Installare cpupower

```bash
sudo apt install linux-cpupower -y
```

## Impostare governor performance

```bash
sudo cpupower frequency-set -g performance
```

Verifica:

```bash
cpupower frequency-info
```

---

# 6. Installazione Ollama

```bash
curl -fsSL https://ollama.com/install.sh | sh
```

Verifica:

```bash
ollama --version
```

---

# 7. Spostare storage modelli su HDD

```bash
sudo mkdir -p /mnt/ai-data/ollama
sudo systemctl stop ollama
sudo mv /usr/share/ollama/* /mnt/ai-data/ollama/
sudo rm -rf /usr/share/ollama
sudo ln -s /mnt/ai-data/ollama /usr/share/ollama
sudo systemctl start ollama
```

---

# 8. Ottimizzazione Ollama

```bash
sudo mkdir -p /etc/systemd/system/ollama.service.d
sudo nano /etc/systemd/system/ollama.service.d/override.conf
```

Contenuto:

```ini
[Service]
Environment="OLLAMA_NUM_PARALLEL=1"
Environment="OLLAMA_MAX_LOADED_MODELS=1"
Environment="OLLAMA_KEEP_ALIVE=24h"
Environment="OLLAMA_HOST=0.0.0.0:11434"
```

Reload:

```bash
sudo systemctl daemon-reload
sudo systemctl restart ollama
```

---

# 9. Installazione Docker

```bash
curl -fsSL https://get.docker.com | sh
sudo usermod -aG docker $USER
```

Logout/login richiesto.

---

# 10. Installazione Open WebUI

```bash
docker run -d \
-p 3000:8080 \
-v open-webui:/app/backend/data \
--name open-webui \
--restart always \
ghcr.io/open-webui/open-webui:main
```

---

# 11. Accesso WebUI

```text
http://IP_SERVER:3000
```

---

# 12. Installazione modelli

## Qwen2.5 Coder 7B

```bash
ollama pull qwen2.5-coder:7b
```

## Qwen2.5 Coder 14B

```bash
ollama pull qwen2.5-coder:14b
```

## DeepSeek Coder

```bash
ollama pull deepseek-coder:6.7b
```

---

# 13. Prestazioni attese

| Modello | Velocità |
|---|---|
| 7B Q4 | 6-15 tok/s |
| 14B | 3-7 tok/s |
| 32B | 1-3 tok/s |

---

# 14. Integrazione VSCode

VSCode:
https://code.visualstudio.com/

Continue:
https://continue.dev/

Config esempio:

```yaml
name: Smart Local Router
version: 1.0.0
schema: v1

models:
  # 🧠 CODING MODEL (DEFAULT)
  - name: DeepSeek Coder
    provider: ollama
    model: deepseek-coder-v2:16b
    apiBase: http://192.168.1.250:11434
    roles:
      - chat
      - edit
      - apply

  # 🤖 AGENT MODEL
  - name: Qwen Agent
    provider: ollama
    model: qwen2.5-coder:14b
    apiBase: http://192.168.1.250:11434
    roles:
      - chat
      - edit
      - apply

context:
  - provider: code
  - provider: diff
  - provider: terminal
  - provider: problems
  - provider: folder
  - provider: repo-map
  - provider: os
```

---

# 15. Installazione Aider

```bash
pip install aider-chat
```

Uso:

```bash
cd progetto
aider
```

Esempi:
- Refactor this class
- Add JWT authentication
- Write unit tests

---

# 16. Struttura consigliata

```text
/mnt/ai-data/
├── models/
├── repos/
├── embeddings/
├── vector-db/
├── backups/
└── datasets/
```

---

# 17. Monitoring

```bash
htop
btop
```

Temperature:

```bash
sudo apt install lm-sensors
sudo sensors-detect
sensors
```

---

# 18. Firewall

```bash
sudo apt install ufw
sudo ufw allow ssh
sudo ufw allow 3000/tcp
sudo ufw allow 11434/tcp
sudo ufw enable
```

---

# 19. Accesso SSH

```bash
ssh utente@IP_SERVER
```

---

# 20. Upgrade futuri

1. SSD più grande
2. RTX 3090
3. NVMe PCIe adapter
4. Più storage

---

# 21. Workflow consigliato

1. VSCode + Continue
2. Ollama locale
3. Aider per refactor
4. Open WebUI per chat
5. Repository indicizzati

---

# 22. Comandi utili

Lista modelli:

```bash
ollama list
```

Eseguire modello:

```bash
ollama run qwen2.5-coder:7b
```

Eliminare modello:

```bash
ollama rm nome-modello
```

Stato servizio:

```bash
systemctl status ollama
```

---

# Fine

Configurazione attuale:

# Skynet.lbs.farm

### Utente
```
user lbsadmin
pwd  <solita>
```

### Modello usato

```bash
ollama pull deepseek-coder-v2:16b
ollama pull qwen2.5-coder:14b
```