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docs: Complete local AI stack documentation
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- Deployed Ollama + Open WebUI on Unraid
- Created custom unraid-assistant model with full infrastructure knowledge:
  - Network topology (8 VLANs, all IPs/gateways)
  - 45+ Docker containers with ports and purposes
  - RouterOS 7 commands and VLAN patterns
  - Traefik labels and Authentik SSO middleware
  - All xtrm-lab.org external URLs
- Added /usr/local/bin/ai terminal helper command
- Documented RAM optimization (stopped 5 containers)
- Added future upgrade notes for Mac Mini M4

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
XTRM-Unraid
2026-01-26 20:38:06 +02:00
parent aee91fcc4b
commit 4066e7ff3a
2 changed files with 101 additions and 29 deletions
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docs/06-CHANGELOG.md
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@@ -3,11 +3,18 @@
## 2026-01-26
### Local AI Stack Deployed
- [AI] Deployed Ollama container with Intel GPU passthrough (/dev/dri)
- [AI] Deployed Ollama container with Intel GPU passthrough
- [AI] Deployed Open WebUI at http://192.168.31.2:3080
- [AI] Installed qwen2.5-coder:7b model (4.7GB)
- [AI] Stopped non-critical containers to free ~4.8GB RAM:
- karakeep, unimus, homarr, netdisco-web, netdisco-backend
- [AI] Installed qwen2.5-coder:7b base model
- [AI] Created custom `unraid-assistant` model with infrastructure knowledge:
- Network topology (all VLANs, IPs, gateways)
- 45+ Docker containers (names, ports, purposes)
- RouterOS 7 commands and patterns
- Traefik labels and Authentik middleware
- All external URLs (xtrm-lab.org)
- [AI] Created `/usr/local/bin/ai` terminal helper command
- [AI] Stopped non-critical containers for RAM: karakeep, unimus, homarr, netdisco-*
### VLAN Activation Attempt & Fixes
- [VLAN] Configured CSS326 switch VLANs via SwOS web interface

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docs/wip/LOCAL-AI-STACK.md
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@@ -13,11 +13,50 @@
| Open WebUI | ✅ Running | http://192.168.31.2:3080 |
| Intel GPU | ✅ Enabled | /dev/dri passthrough |
### Model Installed
### Models Installed
| Model | Size | Type |
|-------|------|------|
| qwen2.5-coder:7b | 4.7 GB | Code-focused LLM |
| qwen2.5-coder:7b | 4.7 GB | Base coding LLM |
| unraid-assistant | 4.7 GB | Custom model with infrastructure knowledge |
---
## Custom Model: unraid-assistant
A fine-tuned system prompt model that knows the xtrm-lab.org infrastructure:
### Knowledge Included
- **Network topology**: All VLANs (10,20,25,30,31,35,40,50), IPs, gateways
- **45+ Docker containers**: Names, images, ports, purposes
- **RouterOS 7**: Commands, VLAN patterns, firewall rules
- **Traefik**: Labels, routing, SSL configuration
- **Authentik**: SSO middleware, provider setup
- **External URLs**: All xtrm-lab.org services
### Usage
```bash
# Terminal (SSH to Unraid)
ai "How do I add a device to the IoT VLAN?"
ai "What port is gitea running on?"
ai "Show me Traefik labels for a new app with Authentik"
# Interactive mode
ai
```
### Rebuild Model
If infrastructure changes, update and rebuild:
```bash
# Edit the Modelfile
nano /mnt/user/appdata/ollama/Modelfile-unraid
# Rebuild
docker exec ollama ollama create unraid-assistant -f /root/.ollama/Modelfile-unraid
```
---
@@ -25,16 +64,21 @@
| Component | Spec |
|-----------|------|
| CPU | Intel N100 |
| CPU | Intel N100 (4 cores) |
| RAM | 16GB (shared with Docker) |
| GPU | Intel UHD (iGPU via /dev/dri) |
| Storage | 1.7TB free on array |
### Performance
- ~1 token/sec with 7B models
- Responses take 30-90 seconds
- Suitable for occasional use, not real-time chat
---
## Containers Stopped for RAM
To free ~4.8GB for AI workloads, these non-critical containers were stopped:
To free ~4.8GB for AI workloads:
| Container | RAM Freed | Purpose |
|-----------|-----------|---------|
@@ -75,30 +119,51 @@ docker run -d \
ghcr.io/open-webui/open-webui:main
```
---
## Usage
### Web Interface
1. Open http://192.168.31.2:3080
2. Create admin account on first visit
3. Select `qwen2.5-coder:7b` model
4. Start chatting
### API Access
### AI Command Helper
```bash
# List models
curl http://192.168.31.2:11434/api/tags
# Generate response (example)
curl http://192.168.31.2:11434/api/generate \
-d '{"model": "qwen2.5-coder:7b", "prompt": "Hello"}'
# /usr/local/bin/ai
#\!/bin/bash
MODEL="unraid-assistant"
if [ $# -eq 0 ]; then
docker exec -it ollama ollama run $MODEL
else
docker exec ollama ollama run $MODEL "$*"
fi
```
---
## Future Considerations
## Open WebUI RAG Setup
- **More RAM:** With 32GB+ RAM, could run larger models (14b, 32b)
- **Dedicated GPU:** Would significantly improve inference speed
- **Additional models:** Can pull more models as needed with `docker exec ollama ollama pull <model>`
For detailed documentation beyond system prompt:
1. Go to http://192.168.31.2:3080
2. **Workspace** → **Knowledge** → **+ Create**
3. Name: `Infrastructure`
4. Upload docs from `/mnt/user/appdata/open-webui/docs/`
Infrastructure docs are pre-copied to that location.
---
## Future: Mac Mini M4 Upgrade
Planning to migrate AI stack to Mac Mini M4 (32GB):
| Metric | N100 (current) | M4 (planned) |
|--------|----------------|--------------|
| Speed | ~1 tok/s | ~15-20 tok/s |
| Max model | 7B | 70B+ |
| Response time | 30-90s | 3-5s |
The M4 unified memory architecture is ideal for LLM inference.
---
## Files
| File | Purpose |
|------|---------|
| /mnt/user/appdata/ollama/Modelfile-unraid | Custom model definition |
| /usr/local/bin/ai | Terminal helper command |
| /mnt/user/appdata/open-webui/docs/ | RAG documents |