nemoclaw-user-get-started

name	nemoclaw-user-get-started
description	Lists the hardware, software, and container runtime requirements for running NemoClaw. Use when verifying prerequisites before installation. Trigger keywords - nemoclaw prerequisites, nemoclaw supported platforms, nemoclaw hardware software, nemoclaw quickstart, install nemoclaw openclaw sandbox, nemoclaw windows wsl2 setup, nemoclaw install windows docker desktop.

NemoClaw Prerequisites

Gotchas

• Ollama binds to 0.0.0.0 so the sandbox can reach it through Docker.

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

Note: Make sure you have completed reviewing the Prerequisites (use the nemoclaw-user-get-started skill) before following this guide.

Step 1: 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 (use the nemoclaw-user-configure-inference skill).

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.

:::{dropdown} Option 1: NVIDIA Endpoints :icon: server

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, Kimi K2.5, 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. :::

:::{dropdown} Option 2: OpenAI :icon: server

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. :::

:::{dropdown} Option 3: Other OpenAI-Compatible Endpoint :icon: link-external

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. :::

:::{dropdown} Option 4: Anthropic :icon: server

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. :::

:::{dropdown} Option 5: Other Anthropic-Compatible Endpoint :icon: link-external

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. :::

:::{dropdown} Option 6: Google Gemini :icon: server

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. :::

:::{dropdown} Option 7: Local Ollama :icon: cpu

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 (use the nemoclaw-user-configure-inference skill).

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. :::

:::{dropdown} Experimental: Local NIM and Local vLLM :icon: beaker

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 (use the nemoclaw-user-configure-inference skill). :::

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 (stored in ~/.nemoclaw/credentials.json)
  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).

Step 2: 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. Override the port with CHAT_UI_URL at onboard time — the dashboard port is derived automatically.

$ nemoclaw onboard                                            # first sandbox uses 18789
$ CHAT_UI_URL=http://127.0.0.1:19000 nemoclaw onboard         # second sandbox uses 19000

You can also use NEMOCLAW_DASHBOARD_PORT directly if you prefer:

$ NEMOCLAW_DASHBOARD_PORT=19000 nemoclaw onboard

For full details on port conflicts and overrides, refer to Port already in use (use the nemoclaw-user-reference skill).

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 (use the nemoclaw-user-deploy-remote skill). Set CHAT_UI_URL to the origin the browser uses before running onboard, so the gateway's CORS allowlist accepts the remote browser.

Step 3: 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

Step 4: 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 (use the nemoclaw-user-configure-inference skill) for provider-specific model IDs and API compatibility notes.

Reset a Stored Credential

If an API key was entered incorrectly during onboarding, clear the stored value and re-enter it on the next onboard run:

$ nemoclaw credentials list           # see which keys are stored
$ nemoclaw credentials reset <KEY>    # clear a single key, for example NVIDIA_API_KEY
$ nemoclaw onboard                    # re-run to re-enter the cleared key

The credentials command is documented in full at nemoclaw credentials reset <KEY> (use the nemoclaw-user-reference skill).

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 (use the nemoclaw-user-reference skill) 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 (use the nemoclaw-user-reference skill) for usage details and flags.

Step 5: 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 (use the nemoclaw-user-reference skill).

References

• Load references/prerequisites.md when verifying prerequisites before installation. Lists the hardware, software, and container runtime requirements for running NemoClaw.
• Load references/windows-preparation.md when preparing a Windows machine for NemoClaw, enabling WSL 2, configuring Docker Desktop for Windows, or troubleshooting a Windows-specific install error. Covers Windows-only preparation steps required before the Quickstart.

Related Skills

• nemoclaw-user-configure-inference — Switch inference providers (use the nemoclaw-user-configure-inference skill) to use a different model or endpoint
• nemoclaw-user-manage-policy — Approve or deny network requests (use the nemoclaw-user-manage-policy skill) when the agent tries to reach external hosts
• nemoclaw-user-deploy-remote — Deploy to a remote GPU instance (use the nemoclaw-user-deploy-remote skill) for always-on operation
• nemoclaw-user-monitor-sandbox — Monitor sandbox activity (use the nemoclaw-user-monitor-sandbox skill) through the OpenShell TUI
• nemoclaw-user-reference — Consult the troubleshooting guide (use the nemoclaw-user-reference skill) for common error messages and resolution steps