NemoClaw with Nemotron 3 Super and Telegram on DGX Spark

Phase 1: Prerequisites

These steps prepare a fresh DGX Spark for NemoClaw. If Docker, the NVIDIA runtime, and Ollama are already configured, skip to Phase 2.

Configure Docker and the NVIDIA container runtime

OpenShell's gateway runs k3s inside Docker. On DGX Spark (Ubuntu 24.04, cgroup v2), Docker must be configured with the NVIDIA runtime and host cgroup namespace mode.

Configure the NVIDIA container runtime for Docker:

sudo nvidia-ctk runtime configure --runtime=docker

Set the cgroup namespace mode required by OpenShell on DGX Spark:

sudo python3 -c "
import json, os
path = '/etc/docker/daemon.json'
d = json.load(open(path)) if os.path.exists(path) else {}
d['default-cgroupns-mode'] = 'host'
json.dump(d, open(path, 'w'), indent=2)
"

Restart Docker:

sudo systemctl restart docker

Verify the NVIDIA runtime works:

docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi

If you get a permission denied error on docker, add your user to the Docker group and activate the new group in your current session:

sudo usermod -aG docker $USER
newgrp docker

This applies the group change immediately. Alternatively, you can log out and back in instead of running newgrp docker.

Install Ollama

Install Ollama:

curl -fsSL https://ollama.com/install.sh | sh

Configure Ollama to listen on all interfaces so the sandbox container can reach it:

sudo mkdir -p /etc/systemd/system/ollama.service.d
printf '[Service]\nEnvironment="OLLAMA_HOST=0.0.0.0"\n' | sudo tee /etc/systemd/system/ollama.service.d/override.conf
sudo systemctl daemon-reload
sudo systemctl restart ollama

Verify it is running and reachable on all interfaces:

curl http://0.0.0.0:11434

Expected: Ollama is running. If not, start it with sudo systemctl start ollama.

Pull the Nemotron 3 Super model

Download Nemotron 3 Super 120B (~87 GB; may take 15--30 minutes depending on network speed):

ollama pull nemotron-3-super:120b

Run it briefly to pre-load weights into memory (type /bye to exit):

ollama run nemotron-3-super:120b

Verify the model is available:

ollama list

You should see nemotron-3-super:120b in the output.

Phase 2: Install and Run NemoClaw

Install NemoClaw

This single command handles everything: installs Node.js (if needed), installs OpenShell, clones the latest stable NemoClaw release, builds the CLI, and runs the onboard wizard to create a sandbox.

curl -fsSL https://www.nvidia.com/nemoclaw.sh | bash

The onboard wizard walks you through setup:

1. Sandbox name -- Pick a name (e.g. my-assistant). Names must be lowercase alphanumeric with hyphens only.
2. Inference provider -- Select Local Ollama (option 7).
3. Model -- Select nemotron-3-super:120b (option 1).
4. Policy presets -- Accept the suggested presets when prompted (hit Y).

When complete you will see output like:

──────────────────────────────────────────────────
Dashboard    http://localhost:18789/
Sandbox      my-assistant (Landlock + seccomp + netns)
Model        nemotron-3-super:120b (Local Ollama)
──────────────────────────────────────────────────
Run:         nemoclaw my-assistant connect
Status:      nemoclaw my-assistant status
Logs:        nemoclaw my-assistant logs --follow
──────────────────────────────────────────────────

Connect to the sandbox and verify inference

Connect to the sandbox:

nemoclaw my-assistant connect

You will see sandbox@my-assistant:~$ -- you are now inside the sandboxed environment.

Verify that the inference route is working:

curl -sf https://inference.local/v1/models

Expected: JSON listing nemotron-3-super:120b.

Talk to the agent (CLI)

Still inside the sandbox, send a test message:

openclaw agent --agent main --local -m "hello" --session-id test

The agent will respond using Nemotron 3 Super. First responses may take 30--90 seconds for a 120B parameter model running locally.

Interactive TUI

Launch the terminal UI for an interactive chat session:

openclaw tui

Press Ctrl+C to exit the TUI.

Exit the sandbox and access the Web UI

Exit the sandbox to return to the host:

exit

If accessing the Web UI directly on the Spark (keyboard and monitor attached), open a browser and navigate to the tokenized URL from Step 4:

http://127.0.0.1:18789/#token=<long-token-here>

If accessing the Web UI from a remote machine, you need to set up port forwarding.

First, find your Spark's IP address. On the Spark, run:

hostname -I | awk '{print $1}'

This prints the primary IP address (e.g. 192.168.1.42). You can also find it in Settings > Wi-Fi or Settings > Network on the Spark's desktop, or check your router's connected-devices list.

Start the port forward on the Spark host:

openshell forward start 18789 my-assistant --background

Then from your remote machine, create an SSH tunnel to the Spark (replace <your-spark-ip> with the IP address from above):

ssh -L 18789:127.0.0.1:18789 <your-user>@<your-spark-ip>

Now open the tokenized URL in your remote machine's browser:

http://127.0.0.1:18789/#token=<long-token-here>

Phase 3: Telegram Bot

Create a Telegram bot

Open Telegram, find @BotFather, send /newbot, and follow the prompts. Copy the bot token it gives you.

Configure and start the Telegram bridge

Make sure you are on the host (not inside the sandbox). If you are inside the sandbox, run exit first.

Set the required environment variables. Replace the placeholders with your actual values. SANDBOX_NAME must match the sandbox name you chose during the onboard wizard:

export TELEGRAM_BOT_TOKEN=<your-bot-token>
export SANDBOX_NAME=my-assistant
export NVIDIA_API_KEY=<your-nvidia-api-key>

Add the Telegram network policy to the sandbox:

nemoclaw my-assistant policy-add

When prompted, select telegram and hit Y to confirm.

Start the Telegram bridge.

export TELEGRAM_BOT_TOKEN=<your-bot-token>
nemoclaw start

The Telegram bridge starts only when the TELEGRAM_BOT_TOKEN environment variable is set. Verify the services are running:

nemoclaw status

Open Telegram, find your bot, and send it a message. The bot forwards it to the agent and replies.

nemoclaw stop
export TELEGRAM_BOT_TOKEN=<your-bot-token>
nemoclaw start

Phase 4: Cleanup and Uninstall

Stop services

Stop any running auxiliary services (Telegram bridge, cloudflared tunnel):

nemoclaw stop

Stop the port forward:

openshell forward list          # find active forwards
openshell forward stop 18789    # stop the dashboard forward

Uninstall NemoClaw

Run the uninstaller from the cloned source directory. It removes all sandboxes, the OpenShell gateway, Docker containers/images/volumes, the CLI, and all state files. Docker, Node.js, npm, and Ollama are preserved.

cd ~/.nemoclaw/source
./uninstall.sh

Uninstaller flags:

To remove everything including the Ollama model:

./uninstall.sh --yes --delete-models

The uninstaller runs 6 steps:

1. Stop NemoClaw helper services and port-forward processes
2. Delete all OpenShell sandboxes, the NemoClaw gateway, and providers
3. Remove the global nemoclaw npm package
4. Remove NemoClaw/OpenShell Docker containers, images, and volumes
5. Remove Ollama models (only with --delete-models)
6. Remove state directories (~/.nemoclaw, ~/.config/openshell, ~/.config/nemoclaw) and the OpenShell binary

Useful commands