How do I install the Nvidia Nemotron Voice Agent Deploy skill?

Run npx skillmds@latest add autohandai-community-skills/nvidia-nemotron-voice-agent-deploy in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Nvidia Nemotron Voice Agent Deploy safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Nvidia Nemotron Voice Agent Deploy?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Nvidia Nemotron Voice Agent Deploy free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under Apache-2.

Who published Nvidia Nemotron Voice Agent Deploy?

autohandai (@autohandai-community-skills) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Nvidia Nemotron Voice Agent Deploy by autohandai-community-skills

Name: Nvidia Nemotron Voice Agent Deploy
Rating: 4.5 (4 reviews)
Author: autohandai

File contents

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.

---name: nvidia-nemotron-voice-agent-deploydescription: 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---# Nemotron Voice Agent DeploymentReal-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```bashnvidia-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)```bashcd nemotron-voice-agentgit submodule update --initcp config/env.example .env```Export your NVIDIA API key:```bashexport NVIDIA_API_KEY=your-api-key # Get from https://build.nvidia.com```Then edit `.env`:```bashNVIDIA_LLM_MODEL=nvidia/nemotron-3-nano-30b-a3b # Cloud model name```**If user requests WebSocket transport**, also add to `.env`:```bashTRANSPORT=WEBSOCKET``````bashdocker 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`:```bashENABLE_MULTILINGUAL=trueASR_CLOUD_FUNCTION_ID=71203149-d3b7-4460-8231-1be2543a1fcaASR_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)```bashuname -m # x86_64 → Workstation, aarch64 → Jetsoncat /etc/nv_tegra_release 2>/dev/null && echo "Jetson"```| Platform | Reference | Requirements ||----------|-----------|--------------|| Workstation (x86_64) | [workstation-deployment.md](references/workstation-deployment.md) | 2x GPU (24GB+ VRAM), NIM containers || Jetson Thor (aarch64) | [jetson-deployment.md](references/jetson-deployment.md) | JetPack 7.0, Nemotron Speech ASR and TTS, vLLM |> **Note:** Multilingual mode available on Workstation with WebRTC transport only.

Frequently asked questions

Nvidia Nemotron Voice Agent Deploy