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# RunPod Template Setup Guide
This guide explains how to deploy the AI Orchestrator (ComfyUI + vLLM) on RunPod using a custom Docker template and network volume.
## Architecture Overview
The deployment uses a **two-tier strategy**:
1. **Docker Image** (software layer) - Contains system packages, Supervisor, Tailscale
2. **Network Volume** (data layer) - Contains models, ComfyUI installation, venvs, configuration
This approach allows fast pod deployment (~2-3 minutes) while keeping all large files (models, ~80-200GB) on a persistent network volume.
## Prerequisites
- RunPod account with credits
- Docker Hub account (for hosting the template image)
- HuggingFace account with API token (for model downloads)
- Tailscale account with auth key (optional, for VPN access)
## Step 1: Build and Push Docker Image
### Option A: Automated Build (Recommended)
The repository includes a Gitea workflow that automatically builds and pushes the Docker image to your Gitea container registry when you push to the `main` branch or create a version tag.
1. **Configure Gitea Secret:**
- Go to your Gitea repository → Settings → Secrets
- Add `REGISTRY_TOKEN` = your Gitea access token with registry permissions
- (The workflow automatically uses your Gitea username via `gitea.actor`)
2. **Trigger Build:**
```bash
# Push to main branch
git push origin main
# Or create a version tag
git tag v1.0.0
git push origin v1.0.0
```
3. **Monitor Build:**
- Go to Actions tab in Gitea
- Wait for build to complete (~5-10 minutes)
- Note the Docker image name: `dev.pivoine.art/valknar/runpod-ai-orchestrator:latest`
### Option B: Manual Build
If you prefer to build manually:
```bash
# From the repository root
cd /path/to/runpod
# Build the image
docker build -t dev.pivoine.art/valknar/runpod-ai-orchestrator:latest .
# Login to your Gitea registry
docker login dev.pivoine.art
# Push to Gitea registry
docker push dev.pivoine.art/valknar/runpod-ai-orchestrator:latest
```
## Step 2: Create Network Volume
Network volumes persist your models and data across pod restarts and rebuilds.
1. **Go to RunPod Dashboard → Storage → Network Volumes**
2. **Click "New Network Volume"**
3. **Configure:**
- **Name**: `ai-orchestrator-models`
- **Size**: `200GB` (adjust based on your needs)
- Essential models only: ~80GB
- All models: ~137-200GB
- **Datacenter**: Choose closest to you (volume tied to datacenter)
4. **Click "Create Volume"**
5. **Note the Volume ID** (e.g., `vol-abc123def456`) for pod deployment
### Storage Requirements
| Configuration | Size | Models Included |
|--------------|------|-----------------|
| Essential | ~80GB | FLUX Schnell, 1-2 SDXL checkpoints, MusicGen Medium |
| Complete | ~137GB | All image/video/audio models from playbook |
| Full + vLLM | ~200GB | Complete + Qwen 2.5 7B + Llama 3.1 8B |
## Step 3: Create RunPod Template
1. **Go to RunPod Dashboard → Templates**
2. **Click "New Template"**
3. **Configure Template Settings:**
**Container Configuration:**
- **Template Name**: `AI Orchestrator (ComfyUI + vLLM)`
- **Template Type**: Docker
- **Container Image**: `dev.pivoine.art/valknar/runpod-ai-orchestrator:latest`
- **Container Disk**: `50GB` (for system and temp files)
- **Docker Command**: Leave empty (uses default `/start.sh`)
**Volume Configuration:**
- **Volume Mount Path**: `/workspace`
- **Attach to Network Volume**: Select your volume ID from Step 2
**Port Configuration:**
- **Expose HTTP Ports**: `8188, 9000, 9001`
- `8188` - ComfyUI web interface
- `9000` - Model orchestrator API
- `9001` - Supervisor web UI
- **Expose TCP Ports**: `22` (SSH access)
**Environment Variables:**
```
HF_TOKEN=your_huggingface_token_here
TAILSCALE_AUTHKEY=tskey-auth-your_tailscale_authkey_here
SUPERVISOR_BACKEND_HOST=localhost
SUPERVISOR_BACKEND_PORT=9001
```
**Advanced Settings:**
- **Start Jupyter**: No
- **Start SSH**: Yes (handled by base image)
4. **Click "Save Template"**
## Step 4: First Deployment (Initial Setup)
The first time you deploy, you need to set up the network volume with models and configuration.
### 4.1 Deploy Pod
1. **Go to RunPod Dashboard → Pods**
2. **Click "Deploy"** or "GPU Pods"
3. **Select your custom template**: `AI Orchestrator (ComfyUI + vLLM)`
4. **Configure GPU:**
- **GPU Type**: RTX 4090 (24GB VRAM) or higher
- **Network Volume**: Select your volume from Step 2
- **On-Demand vs Spot**: Choose based on budget
5. **Click "Deploy"**
### 4.2 SSH into Pod
```bash
# Get pod SSH command from RunPod dashboard
ssh root@<pod-ip> -p <port> -i ~/.ssh/id_ed25519
# Or use RunPod web terminal
```
### 4.3 Initial Setup on Network Volume
```bash
# 1. Clone the repository to /workspace/ai
cd /workspace
git clone https://github.com/your-username/runpod.git ai
cd ai
# 2. Create .env file with your credentials
cp .env.example .env
nano .env
# Edit and add:
# HF_TOKEN=your_huggingface_token
# TAILSCALE_AUTHKEY=tskey-auth-your_key
# GPU_TAILSCALE_IP=<will be set automatically>
# 3. Download essential models (this takes 30-60 minutes)
ansible-playbook playbook.yml --tags comfyui-essential
# OR download all models (1-2 hours)
ansible-playbook playbook.yml --tags comfyui-models-all
# 4. Link models to ComfyUI
bash scripts/link-comfyui-models.sh
# OR if arty is available
arty run models/link-comfyui
# 5. Install ComfyUI custom nodes dependencies
cd /workspace/ComfyUI/custom_nodes/ComfyUI-Manager
pip install -r requirements.txt
cd /workspace/ai
# 6. Restart the container to apply all changes
exit
# Go to RunPod dashboard → Stop pod → Start pod
```
### 4.4 Verify Services
After restart, SSH back in and check:
```bash
# Check supervisor status
supervisorctl -c /workspace/supervisord.conf status
# Expected output:
# comfyui RUNNING pid 123, uptime 0:01:00
# (orchestrator is disabled by default - enable for vLLM)
# Test ComfyUI
curl -I http://localhost:8188
# Test Supervisor web UI
curl -I http://localhost:9001
```
## Step 5: Subsequent Deployments
After initial setup, deploying new pods is quick (2-3 minutes):
1. **Deploy pod** with same template + network volume
2. **Wait for startup** (~1-2 minutes for services to start)
3. **Access services:**
- ComfyUI: `http://<pod-ip>:8188`
- Supervisor: `http://<pod-ip>:9001`
**All models, configuration, and data persist on the network volume!**
## Step 6: Access Services
### Via Direct IP (HTTP)
Get pod IP and ports from RunPod dashboard:
```
ComfyUI: http://<pod-ip>:8188
Supervisor UI: http://<pod-ip>:9001
Orchestrator API: http://<pod-ip>:9000
SSH: ssh root@<pod-ip> -p <port>
```
### Via Tailscale VPN (Recommended)
If you configured `TAILSCALE_AUTHKEY`, the pod automatically joins your Tailscale network:
1. **Get Tailscale IP:**
```bash
ssh root@<pod-ip> -p <port>
tailscale ip -4
# Example output: 100.114.60.40
```
2. **Access via Tailscale:**
```
ComfyUI: http://<tailscale-ip>:8188
Supervisor: http://<tailscale-ip>:9001
Orchestrator: http://<tailscale-ip>:9000
SSH: ssh root@<tailscale-ip>
```
3. **Update LiteLLM config** on your VPS with the Tailscale IP
## Service Management
### Start/Stop Services
```bash
# Start all services
supervisorctl -c /workspace/supervisord.conf start all
# Stop all services
supervisorctl -c /workspace/supervisord.conf stop all
# Restart specific service
supervisorctl -c /workspace/supervisord.conf restart comfyui
# View status
supervisorctl -c /workspace/supervisord.conf status
```
### Enable vLLM Models (Text Generation)
By default, only ComfyUI runs (to save VRAM). To enable vLLM:
1. **Stop ComfyUI** (frees up VRAM):
```bash
supervisorctl -c /workspace/supervisord.conf stop comfyui
```
2. **Start orchestrator** (manages vLLM models):
```bash
supervisorctl -c /workspace/supervisord.conf start orchestrator
```
3. **Test text generation:**
```bash
curl -X POST http://localhost:9000/v1/chat/completions \
-H 'Content-Type: application/json' \
-d '{"model":"qwen-2.5-7b","messages":[{"role":"user","content":"Hello"}]}'
```
### Switch Back to ComfyUI
```bash
# Stop orchestrator (stops all vLLM models)
supervisorctl -c /workspace/supervisord.conf stop orchestrator
# Start ComfyUI
supervisorctl -c /workspace/supervisord.conf start comfyui
```
## Updating the Template
When you make changes to code or configuration:
### Update Docker Image
```bash
# 1. Make changes to Dockerfile or start.sh
# 2. Push to repository
git add .
git commit -m "Update template configuration"
git push origin main
# 3. Gitea workflow auto-builds new image
# 4. Terminate old pod and deploy new one with updated image
```
### Update Network Volume Data
```bash
# SSH into running pod
ssh root@<pod-ip> -p <port>
# Update repository
cd /workspace/ai
git pull
# Re-run Ansible if needed
ansible-playbook playbook.yml --tags <specific-tag>
# Restart services
supervisorctl -c /workspace/supervisord.conf restart all
```
## Troubleshooting
### Pod fails to start
**Check logs:**
```bash
# Via SSH
cat /workspace/logs/supervisord.log
cat /workspace/logs/comfyui.err.log
# Via RunPod web terminal
tail -f /workspace/logs/*.log
```
**Common issues:**
- Missing `.env` file → Create `/workspace/ai/.env` with required vars
- Supervisor config not found → Ensure `/workspace/ai/supervisord.conf` exists
- Port conflicts → Check if services are already running
### Tailscale not connecting
**Check Tailscale status:**
```bash
tailscale status
tailscale ip -4
```
**Common issues:**
- Missing or invalid `TAILSCALE_AUTHKEY` in `.env`
- Auth key expired → Generate new key in Tailscale admin
- Firewall blocking → RunPod should allow Tailscale by default
### Services not starting
**Check Supervisor:**
```bash
supervisorctl -c /workspace/supervisord.conf status
supervisorctl -c /workspace/supervisord.conf tail -f comfyui
```
**Common issues:**
- venv broken → Re-run `scripts/bootstrap-venvs.sh`
- Models not downloaded → Run Ansible playbook again
- Python version mismatch → Rebuild venvs
### Out of VRAM
**Check GPU memory:**
```bash
nvidia-smi
```
**RTX 4090 (24GB) capacity:**
- ComfyUI (FLUX Schnell): ~23GB (can't run with vLLM)
- vLLM (Qwen 2.5 7B): ~14GB
- vLLM (Llama 3.1 8B): ~17GB
**Solution:** Only run one service at a time (see Service Management section)
### Network volume full
**Check disk usage:**
```bash
df -h /workspace
du -sh /workspace/*
```
**Clean up:**
```bash
# Remove old HuggingFace cache
rm -rf /workspace/huggingface_cache
# Re-download essential models only
cd /workspace/ai
ansible-playbook playbook.yml --tags comfyui-essential
```
## Cost Optimization
### Spot vs On-Demand
- **Spot instances**: ~70% cheaper, can be interrupted
- **On-Demand**: More expensive, guaranteed availability
**Recommendation:** Use spot for development, on-demand for production
### Network Volume Pricing
- First 1TB: $0.07/GB/month
- Beyond 1TB: $0.05/GB/month
**200GB volume cost:** ~$14/month
### Pod Auto-Stop
Configure auto-stop in RunPod pod settings to save costs when idle:
- Stop after 15 minutes idle
- Stop after 1 hour idle
- Manual stop only
## Advanced Configuration
### Custom Environment Variables
Add to template or pod environment variables:
```bash
# Model cache locations
HF_HOME=/workspace/huggingface_cache
TRANSFORMERS_CACHE=/workspace/huggingface_cache
# ComfyUI settings
COMFYUI_PORT=8188
COMFYUI_LISTEN=0.0.0.0
# Orchestrator settings
ORCHESTRATOR_PORT=9000
# GPU settings
CUDA_VISIBLE_DEVICES=0
```
### Multiple Network Volumes
You can attach multiple network volumes for organization:
1. **Models volume** - `/workspace/models` (read-only, shared)
2. **Data volume** - `/workspace/data` (read-write, per-project)
### Custom Startup Script
Override `/start.sh` behavior by creating `/workspace/custom-start.sh`:
```bash
#!/bin/bash
# Custom startup commands
# Source default startup
source /start.sh
# Add your custom commands here
echo "Running custom initialization..."
```
## References
- [RunPod Documentation](https://docs.runpod.io/)
- [RunPod Templates Overview](https://docs.runpod.io/pods/templates/overview)
- [Network Volumes Guide](https://docs.runpod.io/storage/network-volumes)
- [ComfyUI Documentation](https://github.com/comfyanonymous/ComfyUI)
- [Supervisor Documentation](http://supervisord.org/)
- [Tailscale Documentation](https://tailscale.com/kb/)
## Support
For issues or questions:
- Check troubleshooting section above
- Review `/workspace/logs/` files
- Check RunPod community forums
- Open issue in project repository