Quickstart#

Follow these steps to get started with NemoClaw and your first sandboxed OpenClaw agent.

Note

Make sure you have completed reviewing the Prerequisites before following this guide.

Install NemoClaw and Onboard OpenClaw Agent#

Download and run the installer script. The script installs Node.js if it is not already present, then runs the guided onboard wizard to create a sandbox, configure inference, and apply security policies.

Note

NemoClaw creates a fresh OpenClaw instance inside the sandbox during the onboarding process.

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

If you use nvm or fnm to manage Node.js, the installer might not update your current shell’s PATH. If nemoclaw is not found after install, run source ~/.bashrc (or source ~/.zshrc for zsh) or open a new terminal.

Note

The onboard flow builds the sandbox image with NEMOCLAW_DISABLE_DEVICE_AUTH=1 so the dashboard is immediately usable during setup. This is a build-time setting baked into the sandbox image, not a runtime knob. If you export NEMOCLAW_DISABLE_DEVICE_AUTH after onboarding finishes, it has no effect on an existing sandbox.

Respond to the Onboard Wizard#

After the installer launches nemoclaw onboard, the wizard walks you through a sandbox name, an inference provider, and a network policy preset. At any prompt, press Enter to accept the default shown in [brackets], type back to return to the previous prompt, or type exit to quit.

The inference provider prompt presents a numbered list.

  1) NVIDIA Endpoints
  2) OpenAI
  3) Other OpenAI-compatible endpoint
  4) Anthropic
  5) Other Anthropic-compatible endpoint
  6) Google Gemini
  7) Local Ollama        (only shown when Ollama is detected on the host)
  Choose [1]:

Pick the option that matches where you want inference traffic to go, then expand the matching helper below for the follow-up prompts and the API key environment variable to set. For the full list of providers and validation behavior, refer to Inference Options.

Tip

Export the API key before launching the installer so the wizard does not have to ask for it. For example, run export NVIDIA_API_KEY=<your-key> before curl ... | bash. If you entered a key incorrectly, refer to Reset a Stored Credential to clear and re-enter it.

Option 1: NVIDIA Endpoints

Routes inference to models hosted on build.nvidia.com.

Use NVIDIA_API_KEY for the API key. Get one from the NVIDIA build API keys page.

Respond to the wizard as follows.

  1. At the Choose [1]: prompt, press Enter (or type 1) to select NVIDIA Endpoints.

  2. At the NVIDIA_API_KEY: prompt, paste your key if it is not already exported.

  3. At the Choose model [1]: prompt, pick a curated model from the list (for example, Nemotron 3 Super 120B, GLM-5.1, MiniMax M2.5, or GPT-OSS 120B), or pick Other… to enter any model ID from the NVIDIA Endpoints catalog.

NemoClaw validates the model against the catalog API before creating the sandbox.

Tip

Use this option for Nemotron and other models hosted on build.nvidia.com. If you run NVIDIA Nemotron from a self-hosted NIM, an enterprise gateway, or any other endpoint, choose Option 3 instead, since all Nemotron models expose OpenAI-compatible APIs.

Option 2: OpenAI

Routes inference to the OpenAI API at https://api.openai.com/v1.

Use OPENAI_API_KEY for the API key. Get one from the OpenAI API keys page.

Respond to the wizard as follows.

  1. At the Choose [1]: prompt, type 2 to select OpenAI.

  2. At the OPENAI_API_KEY: prompt, paste your key if it is not already exported.

  3. At the Choose model [1]: prompt, pick a curated model (for example, gpt-5.4, gpt-5.4-mini, gpt-5.4-nano, or gpt-5.4-pro-2026-03-05), or pick Other… to enter any OpenAI model ID.

Option 3: Other OpenAI-Compatible Endpoint

Routes inference to any server that implements /v1/chat/completions, including OpenRouter, LocalAI, llama.cpp, vLLM behind a proxy, and any compatible gateway.

Use COMPATIBLE_API_KEY for the API key. Set it to whatever credential your endpoint expects. If your endpoint does not require auth, use any non-empty placeholder.

Respond to the wizard as follows.

  1. At the Choose [1]: prompt, type 3 to select Other OpenAI-compatible endpoint.

  2. At the OpenAI-compatible base URL prompt, enter the provider’s base URL. Find the exact value in your provider’s API documentation. NemoClaw appends /v1 automatically, so leave that suffix off.

  3. At the COMPATIBLE_API_KEY: prompt, paste your key if it is not already exported.

  4. At the Other OpenAI-compatible endpoint model []: prompt, enter the model ID exactly as it appears in your provider’s model catalog (for example, openai/gpt-5.4 on OpenRouter).

NemoClaw sends a real inference request to validate the endpoint and model. NemoClaw forces the chat completions API for compatible endpoints because many backends advertise /v1/responses but mishandle the developer role used by the Responses API.

Tip

NVIDIA Nemotron models expose OpenAI-compatible APIs, so this option is the right choice for any Nemotron deployment that does not live on build.nvidia.com. Common examples include a self-hosted NIM container, an enterprise NVIDIA AI Enterprise gateway, or a vLLM/SGLang server running Nemotron weights. Point the base URL at your endpoint and enter the Nemotron model ID exactly as your server reports it.

Option 4: Anthropic

Routes inference to the Anthropic Messages API at https://api.anthropic.com.

Use ANTHROPIC_API_KEY for the API key. Get one from the Anthropic console keys page.

Respond to the wizard as follows.

  1. At the Choose [1]: prompt, type 4 to select Anthropic.

  2. At the ANTHROPIC_API_KEY: prompt, paste your key if it is not already exported.

  3. At the Choose model [1]: prompt, pick a curated model (for example, claude-sonnet-4-6, claude-haiku-4-5, or claude-opus-4-6), or pick Other… to enter any Claude model ID.

Option 5: Other Anthropic-Compatible Endpoint

Routes inference to any server that implements the Anthropic Messages API at /v1/messages, including Claude proxies, Bedrock-compatible gateways, and self-hosted Anthropic-compatible servers.

Use COMPATIBLE_ANTHROPIC_API_KEY for the API key. Set it to whatever credential your endpoint expects.

Respond to the wizard as follows.

  1. At the Choose [1]: prompt, type 5 to select Other Anthropic-compatible endpoint.

  2. At the Anthropic-compatible base URL prompt, enter the proxy or gateway’s base URL from its documentation.

  3. At the COMPATIBLE_ANTHROPIC_API_KEY: prompt, paste your key if it is not already exported.

  4. At the Other Anthropic-compatible endpoint model []: prompt, enter the model ID exactly as it appears in your gateway’s model catalog.

Option 6: Google Gemini

Routes inference to Google’s OpenAI-compatible Gemini endpoint at https://generativelanguage.googleapis.com/v1beta/openai/.

Use GEMINI_API_KEY for the API key. Get one from Google AI Studio API keys.

Respond to the wizard as follows.

  1. At the Choose [1]: prompt, type 6 to select Google Gemini.

  2. At the GEMINI_API_KEY: prompt, paste your key if it is not already exported.

  3. At the Choose model [5]: prompt, pick a curated model (for example, gemini-3.1-pro-preview, gemini-3.1-flash-lite-preview, gemini-3-flash-preview, gemini-2.5-pro, gemini-2.5-flash, or gemini-2.5-flash-lite), or pick Other… to enter any Gemini model ID.

Option 7: Local Ollama

Routes inference to a local Ollama instance on localhost:11434. This option only appears when Ollama is installed or running on the host.

No API key is required. NemoClaw generates a token and starts an authenticated proxy so containers can reach Ollama without exposing it to your network.

Respond to the wizard as follows.

  1. At the Choose [1]: prompt, type 7 to select Local Ollama.

  2. At the Choose model [1]: prompt, pick from Ollama models if any are already installed. If none are installed, pick a starter model to pull and load now, or pick Other… to enter any Ollama model ID.

For setup details, including GPU recommendations and starter model choices, refer to Use a Local Inference Server.

Warning

Ollama binds to 0.0.0.0 so the sandbox can reach it through Docker. On public WiFi, any device on the same network can send prompts to your GPU through the Ollama API. Refer to CNVD-2025-04094 and CVE-2024-37032.

Experimental: Local NIM and Local vLLM

These options appear when NEMOCLAW_EXPERIMENTAL=1 is set and the prerequisites are met.

  • Local NVIDIA NIM requires a NIM-capable GPU. NemoClaw pulls and manages a NIM container.

  • Local vLLM requires a vLLM server already running on localhost:8000. NemoClaw auto-detects the loaded model.

For setup, refer to Use a Local Inference Server.

Review the Configuration Before the Sandbox Build#

After you enter the sandbox name, the wizard prints a review summary and asks for final confirmation before starting the destructive sandbox image build. For example, if you picked NVIDIA Endpoints, the summary looks like the following:

  ──────────────────────────────────────────────────
  Review configuration
  ──────────────────────────────────────────────────
  Provider:      nvidia-api
  Model:         nvidia/nemotron-3-super-120b-a12b
  API key:       NVIDIA_API_KEY (registered with the OpenShell gateway)
  Web search:    disabled
  Messaging:     none
  Sandbox name:  my-assistant
  ──────────────────────────────────────────────────
  Apply this configuration? [Y/n]:

The default is Y, so you can press Enter once to continue. Answer n to abort cleanly, fix the entries, and re-run nemoclaw onboard.

Non-interactive runs (NEMOCLAW_NON_INTERACTIVE=1) print the summary for log clarity but skip the prompt.

When the install completes, a summary confirms the running environment. The Model and provider line reflects the inference option you picked during onboarding. The example below shows the result if you picked NVIDIA Endpoints during onboarding.

──────────────────────────────────────────────────
Sandbox      my-assistant (Landlock + seccomp + netns)
Model        nvidia/nemotron-3-super-120b-a12b (NVIDIA Endpoints)
──────────────────────────────────────────────────
Run:         nemoclaw my-assistant connect
Status:      nemoclaw my-assistant status
Logs:        nemoclaw my-assistant logs --follow
──────────────────────────────────────────────────

[INFO]  === Installation complete ===

If you picked a different option, the Model line shows that provider’s model and label instead. For example, you might see gpt-5.4 (OpenAI), claude-sonnet-4-6 (Anthropic), gemini-2.5-flash (Google Gemini), llama3.1:8b (Local Ollama), or <your-model> (Other OpenAI-compatible endpoint).

Open the OpenClaw UI in a Browser#

The onboard wizard automatically starts an SSH port forward from your host’s 127.0.0.1:18789 to the sandbox dashboard, then prints a tokenized URL in the install summary.

──────────────────────────────────────────────────
OpenClaw UI (tokenized URL; treat it like a password; save it now - it will not be printed again)
Port 18789 must be forwarded before opening these URLs.
Dashboard: http://127.0.0.1:18789/#token=<auth-token>
──────────────────────────────────────────────────

Open that URL in your browser. The #token=<auth-token> fragment authenticates the browser to the sandbox gateway, so save the URL securely and treat it like a password. NemoClaw prints the token only once.

Restart the Port Forward#

If the forward stopped (for example, after a reboot) or you opened a new terminal and the URL no longer responds, restart it manually.

openshell forward start --background 18789 my-assistant

To list active forwards across all sandboxes, run the following command.

openshell forward list

Run Multiple Sandboxes#

Each sandbox needs its own dashboard port, since openshell forward refuses to bind a port that another sandbox is already using. When the default port is already held by another sandbox, nemoclaw onboard scans ports 18789 through 18799 and uses the next free port.

$ nemoclaw onboard                                            # first sandbox uses 18789
$ nemoclaw onboard                                            # second sandbox uses the next free port

To choose a specific port, pass --control-ui-port:

$ nemoclaw onboard --control-ui-port 19000

You can also set CHAT_UI_URL or NEMOCLAW_DASHBOARD_PORT before onboarding:

$ CHAT_UI_URL=http://127.0.0.1:19000 nemoclaw onboard
$ NEMOCLAW_DASHBOARD_PORT=19000 nemoclaw onboard

For full details on port conflicts and overrides, refer to Port already in use.

Open the UI from a Remote Host#

If NemoClaw is running on a remote GPU instance and you want to open the UI from a laptop, refer to Remote Dashboard Access. Set CHAT_UI_URL to the origin the browser uses before running onboard, so the gateway’s CORS allowlist accepts the remote browser.

Chat with the Agent from the Terminal#

If you prefer a terminal-based chat, connect to the sandbox and use the OpenClaw CLI.

nemoclaw my-assistant connect

In the sandbox shell, open the OpenClaw terminal UI and start a chat.

openclaw tui

Alternatively, send a single message and print the response.

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

Reconfigure or Recover#

Recover from a misconfigured sandbox without re-running the full onboard wizard or destroying workspace state.

Change Inference Model or API#

Change the active model or provider at runtime without rebuilding the sandbox:

$ openshell inference set -g nemoclaw --model <model> --provider <provider>

Refer to Switch inference providers for provider-specific model IDs and API compatibility notes.

Reset a Stored Credential#

If a provider credential was entered incorrectly during onboarding, clear the gateway-registered value and re-enter it on the next onboard run:

$ nemoclaw credentials list                # see which providers are registered
$ nemoclaw credentials reset <PROVIDER>    # clear a single provider, for example nvidia-prod
$ nemoclaw onboard                         # re-run to re-enter the cleared provider

The credentials command is documented in full at nemoclaw credentials reset <PROVIDER>.

Rebuild a Sandbox While Preserving Workspace State#

If you changed the underlying Dockerfile, upgraded OpenClaw, or want to pick up a new base image without losing your sandbox’s workspace files, use rebuild instead of destroying and recreating:

$ nemoclaw <sandbox-name> rebuild

Rebuild preserves the mounted workspace and registered policies while recreating the container. Refer to nemoclaw <name> rebuild for flag details.

Add a Network Preset After Onboarding#

Apply an additional preset (for example, Telegram or GitHub) to a running sandbox without re-onboarding:

$ nemoclaw <sandbox-name> policy-add

Refer to nemoclaw <name> policy-add for usage details and flags.

Update to the Latest Version#

When a new NemoClaw release becomes available, update the nemoclaw CLI on your host and check existing sandboxes for stale agent/runtime versions.

Update the NemoClaw CLI#

Re-run the installer. Before it onboards anything, the installer calls nemoclaw backup-all automatically, storing a snapshot of each running sandbox in ~/.nemoclaw/rebuild-backups/ as a safety net.

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

Upgrade sandboxes with stale agent and runtime versions#

The installer checks registered sandboxes after onboarding succeeds and runs nemoclaw upgrade-sandboxes --auto for stale running sandboxes. Use upgrade-sandboxes directly to verify the result, rebuild when you skipped the installer or onboarding step, or handle sandboxes that were stopped or could not be version-checked. The upgrade flow is non-destructive by default because NemoClaw preserves manifest-defined workspace state, but a manual snapshot before any major upgrade gives you a state restore point.

Safe upgrade flow:

$ nemoclaw <sandbox-name> snapshot create --name pre-upgrade   # optional, recommended
$ curl -fsSL https://www.nvidia.com/nemoclaw.sh | bash          # updates CLI; auto-upgrades stale running sandboxes
$ nemoclaw upgrade-sandboxes --check                            # verify or list remaining stale/unknown sandboxes
$ nemoclaw upgrade-sandboxes                                    # manually rebuild remaining stale running sandboxes

For scripted manual rebuilds, use nemoclaw upgrade-sandboxes --auto to skip the confirmation prompt.

If the upgraded sandbox needs its workspace state reverted, restore the pre-upgrade snapshot into the running sandbox. This restores saved state directories only; it does not downgrade the sandbox image or agent/runtime:

$ nemoclaw <sandbox-name> snapshot restore pre-upgrade

What changes during a rebuild#

Each rebuild destroys the existing container and creates a new one. NemoClaw protects your data through the same backup-and-restore flow as nemoclaw <name> rebuild:

  • NemoClaw preserves manifest-defined workspace state. Before deleting the old container, NemoClaw snapshots the state directories defined in the agent manifest (typically /sandbox/.openclaw/workspace/) and restores them into the new container. Stored credentials (~/.nemoclaw/credentials.json) and registered policy presets live on the host and are re-applied to the new sandbox automatically.

  • NemoClaw does not preserve runtime changes outside the workspace state directories. This includes packages installed inside the running container with apt or pip, files in non-workspace paths, and in-memory or process state. If you have customized the running container at runtime, capture that as Dockerfile changes (for nemoclaw onboard --from) or a manual openshell sandbox download before the rebuild starts.

Aborts before the destroy step are non-destructive. The flow refuses to proceed past preflight if a credential is missing (see below) or past backup if the snapshot fails (with "Aborting rebuild to prevent data loss"), so a botched run leaves the original sandbox intact and ready to retry.

See Backup and Restore for the full list of state-preservation guarantees, snapshot retention, and instructions for manual backups when the auto-flow is not enough.

Note

If the rebuild aborts with Missing credential: <KEY> The rebuild preflight reads the provider credential recorded by your last nemoclaw onboard session. If you have switched providers since onboarding (for example, from a remote API to a local Ollama setup) the preflight may still reference the old key and fail before any destroy step runs.

To recover, re-run nemoclaw onboard and select your current provider. This refreshes the session metadata. Your existing container keeps serving traffic until the new image is ready.

Uninstall#

To remove NemoClaw and all resources created during setup, run the CLI’s built-in uninstall command:

nemoclaw uninstall

Flag

Effect

--yes

Skip the confirmation prompt.

--keep-openshell

Leave the openshell binary installed.

--delete-models

Also remove NemoClaw-pulled Ollama models.

nemoclaw uninstall runs the version-pinned uninstall.sh that shipped with your installed CLI, so it does not fetch anything over the network at uninstall time.

If the nemoclaw CLI is missing or broken, fall back to the hosted script:

curl -fsSL https://raw.githubusercontent.com/NVIDIA/NemoClaw/refs/heads/main/uninstall.sh | bash

For a full comparison of the two forms — what they fetch, what they trust, and when to prefer each — see nemoclaw uninstall vs. the hosted uninstall.sh.

Next Steps#