name: nemotron-voice-agent-deploy description: Deploy Nemotron Voice Agent on Workstation (x86), Jetson Thor, or Cloud NIMs. Real-time speech-to-speech using NVIDIA ASR, TTS, LLM with WebRTC/WebSocket transport.
Nemotron Voice Agent Deployment
Real-time conversational AI voice agent using NVIDIA NIMs (ASR, TTS, LLM) with WebRTC (default) or WebSocket transport.
Deployment Flow
Always verify hardware first, even if user mentions a specific platform.
STEP 1: Hardware Detection
nvidia-smi --query-gpu=name,memory.total --format=csv,noheader 2>/dev/null
| Result | Action |
|---|---|
| Command fails / No output | → Cloud NIMs |
| GPU detected | → STEP 2: Platform Detection |
Cloud NIMs (No GPU)
cd nemotron-voice-agent
git submodule update --init
cp config/env.example .env
Export your NVIDIA API key:
export NVIDIA_API_KEY=your-api-key # Get from https://build.nvidia.com
Then edit .env:
NVIDIA_LLM_MODEL=nvidia/nemotron-3-nano-30b-a3b # Cloud model name
If user requests WebSocket transport, also add to .env:
TRANSPORT=WEBSOCKET
docker compose up --build --no-deps -d python-app ui-app
# WebRTC: http://localhost:9000
# WebSocket: http://localhost:7860/static/index.html
Note: Deployment may take 30-60 minutes on first run.
If user requests Multilingual mode, also add to .env:
ENABLE_MULTILINGUAL=true
ASR_CLOUD_FUNCTION_ID=71203149-d3b7-4460-8231-1be2543a1fca
ASR_MODEL_NAME=parakeet-rnnt-1.1b-unified-ml-cs-universal-multi-asr-streaming
Remote Access: ssh -L 9000:localhost:9000 user@host or http://<HOST_IP>:9000
STEP 2: Platform Detection (if GPU detected)
uname -m # x86_64 → Workstation, aarch64 → Jetson
cat /etc/nv_tegra_release 2>/dev/null && echo "Jetson"
| Platform | Reference | Requirements |
|---|---|---|
| Workstation (x86_64) | workstation-deployment.md | 2x GPU (24GB+ VRAM), NIM containers |
| Jetson Thor (aarch64) | jetson-deployment.md | JetPack 7.0, Nemotron Speech ASR and TTS, vLLM |
Note: Multilingual mode available on Workstation with WebRTC transport only.