Quickstart with LangChain Deep Agents Code
Quickstart with LangChain Deep Agents Code
Use this guide when you want NemoClaw to build an OpenShell sandbox with the dcode terminal coding agent installed and configured for NemoClaw-managed inference.
Onboard
Run onboarding with the canonical agent ID.
The image installs a hash-locked, pinned Deep Agents Code release with NVIDIA provider support.
NemoClaw writes /sandbox/.deepagents/config.toml with an OpenAI-compatible provider pointed at https://inference.local/v1, uses a scoped placeholder API key for that managed route, and sets use_responses_api = false for Chat Completions compatibility.
NemoClaw/OpenShell keeps real provider credentials in credential handling and does not write them into the Deep Agents config file.
Use the Harness
Connect to the sandbox, then launch the terminal UI.
For a single headless task, run:
The managed wrapper launches Deep Agents Code with HOME=/sandbox, update checks disabled, remote Deep Agents sandbox providers disabled, MCP auto-loading disabled, and shell allow-list overrides blocked.
State and Backup
Deep Agents Code state lives under /sandbox/.deepagents.
NemoClaw snapshot and rebuild flows preserve the app state directory, skills, generated config, and hooks config when those files exist.
NemoClaw intentionally does not preserve .env or .mcp.json because users may put Tavily, LangSmith, MCP service, or provider credentials there, and this managed harness disables MCP at runtime.
Optional Web Search
Deep Agents Code can use Tavily web search when you provide a Tavily credential in the runtime environment. NemoClaw does not enable Tavily or LangSmith by default for this harness. Before you provide those credentials, add the required egress endpoints to the sandbox policy so optional integrations stay explicit.
Troubleshooting
Use normal sandbox lifecycle commands:
status reports the selected harness as a terminal runtime and prints the interactive/headless command shape.
There is no dashboard port or long-running gateway process for this harness.
Next Steps
- Inference Options to choose a provider and model.
- Backup and Restore for snapshot and rebuild preservation details.
- Runtime Controls for sandbox mutability and host-side control boundaries.
- Troubleshooting for common setup and runtime issues.