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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.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/autohandai/community-skills --skill nvidia-nemotron-voice-agent-deploy명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Build, convert, validate, and install Autohand extensions, including Pi adaptations.
Run Weizhena's Deep Research workflow in Autohand Code for outline generation, deep web investigation, structured evidence capture, and final research reports.
Use Aaronontheweb dotnet-skills for Claude Code-oriented .NET maintenance, refactoring, and agent workflows.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | nvidia-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. |
| license | Apache-2.0 AND CC-BY-4.0 |
| metadata | {"author":"NVIDIA"} |
Real-time conversational AI voice agent using NVIDIA NIMs (ASR, TTS, LLM) with WebRTC (default) or WebSocket transport.
Always verify hardware first, even if user mentions a specific platform.
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 |
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
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.