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gianni-dalerta c965f22f03 Add deployment scripts and RunPod guide

- deploy/runpod/README.md - Full RunPod deployment guide
- scripts/generate_master_key.py - Generate secure admin keys
- scripts/download_models.py - Pre-download Whisper models

Deployment options documented:
- RunPod GPU (/bin/zsh.44/hr for RTX 4090)
- Docker Compose (local GPU/CPU)
- Cost optimization tips

2026-01-30 13:44:16 -05:00

README.md

Add deployment scripts and RunPod guide

2026-01-30 13:44:16 -05:00

README.md

Deploy OpenClaw Voice on RunPod

Deploy OpenClaw Voice on RunPod for GPU-accelerated voice inference.

Quick Deploy

1. Create a RunPod Account

2. Deploy from Template

Use our pre-built template:

Template ID: openclaw-voice
Docker Image: ghcr.io/purple-horizons/openclaw-voice:latest

Or deploy manually:

3. Manual Deployment

Create a new Pod:

GPU: RTX 4090 recommended ($0.44/hr)
Docker Image: ghcr.io/purple-horizons/openclaw-voice:latest
Expose Port: 8765
Volume: 20GB (for model cache)

Environment Variables:

OPENCLAW_STT_MODEL=large-v3-turbo
OPENCLAW_STT_DEVICE=cuda
OPENCLAW_REQUIRE_AUTH=true
OPENCLAW_MASTER_KEY=<generate-a-secure-key>
OPENAI_API_KEY=<your-openai-key>

4. Connect

Once deployed, get your Pod's public URL:

wss://<pod-id>-8765.proxy.runpod.net/ws?api_key=<your-key>

Cost Optimization

On-Demand (Pay per hour)

RTX 4090: ~$0.44/hr
RTX 3090: ~$0.30/hr
A10: ~$0.50/hr

Spot Instances (Up to 80% cheaper)

Use spot instances for non-critical workloads
May be interrupted with 30s notice

Reserved (Best for production)

Reserve a GPU for consistent pricing
No interruptions

Scaling

Single Pod

Handles ~10-20 concurrent voice sessions
Good for testing and small deployments

Multiple Pods with Load Balancer

Deploy 2+ pods
Use RunPod's serverless endpoints
Or put behind Cloudflare Load Balancer

Monitoring

Health Check

curl https://<pod-url>/

Check Logs

runpodctl logs <pod-id>

Troubleshooting

GPU Not Detected

Ensure NVIDIA drivers are loaded
Check nvidia-smi in pod terminal

Out of Memory

Reduce batch size
Use smaller Whisper model (base vs large)
Upgrade to GPU with more VRAM

High Latency

Use larger GPU
Enable streaming responses
Check network latency to RunPod region