Deploys an already-built NAT agent as a policy-governed OpenShell sandbox on a local NeMo Platform, so the same agent image gets Landlock filesystem isolation and a pure default-deny network policy (the sandbox reaches nothing on the network directly; its model calls are brokered by the OpenShell gateway through the inference.local route) for free. Covers the proven wire-inference.local -> package -> DeploymentConfig -> deploy (executor openshell-local) -> wait -> query -> zero-egress proof -> cleanup flow. Use when the user asks to deploy an agent as a sandbox, sandbox a deployment, run an agent under a Landlock/egress policy, or use the openshell-local executor. Trigger keywords - deploy sandbox, sandboxed agent, openshell deployment, openshell-local executor, sandbox policy, egress policy, landlock, governed deployment, network egress governance, inference.local.
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Deploys an already-built NAT agent as a policy-governed OpenShell sandbox on a local NeMo Platform, so the same agent image gets Landlock filesystem isolation and a pure default-deny network policy (the sandbox reaches nothing on the network directly; its model calls are brokered by the OpenShell gateway through the inference.local route) for free. Covers the proven wire-inference.local -> package -> DeploymentConfig -> deploy (executor openshell-local) -> wait -> query -> zero-egress proof -> cleanup flow. Use when the user asks to deploy an agent as a sandbox, sandbox a deployment, run an agent under a Landlock/egress policy, or use the openshell-local executor. Trigger keywords - deploy sandbox, sandboxed agent, openshell deployment, openshell-local executor, sandbox policy, egress policy, landlock, governed deployment, network egress governance, inference.local.
triggers
["deploy the agent as a sandbox","sandbox the deployment","deploy with openshell","openshell-local executor","run the agent under an egress policy","governed sandbox deployment","landlock the agent"]
not-for
["nemo-build-agent (use to scaffold + build the agent image first)","nemo-try-agent (use to query an already-deployed agent)","nemo-setup (use to install and start the platform first)","nemo-status (use for a read-only health dashboard)"]
compatibility
nemo-platform >= 0.1.0; requires the nemo-deployments plugin installed with the openshell extra (`openshell>=0.0.92` from PyPI); a running OpenShell docker-driver gateway on :17670 (not :8080, which the platform owns) whose JWT signing keys were generated once with `generate-certs`; a NeMo Platform reachable from inside a sandbox at the sandbox network's gateway address (`--host 0.0.0.0`) with the `openshell-local` executor loaded via `--config packages/nmp_platform/config/local.yaml`; the gateway's `inference.local` route wired to the platform Inference Gateway (`openshell provider create` + `openshell inference set`); the agents plugin for the packaging step. Docker-driver specific (sandboxes reach the platform at `host.openshell.internal:8080`). Linux (glibc >= 2.39) only: verified live end-to-end there, and the `inference.local` hop is unverified on macOS (Docker Desktop resolves the sandbox's `host.openshell.internal` inside its Linux VM, not to the Mac's loopback).
maturity
experimental
license
Apache-2.0
user-invocable
true
allowed-tools
["Bash","Read","Write","Edit"]
Deploy an agent as a governed OpenShell sandbox
Deploy an ordinary NAT agent through the standard NeMo deployments API, but with the executor set to openshell-local so the agent runs inside an OpenShell sandbox under an automatically generated SandboxPolicy: Landlock filesystem isolation, run_as_user: sandbox, and a pure default-deny network policy. The agent reaches models through OpenShell's gateway-managed inference.local route, so the sandbox itself is granted no direct network egress at all: the model call is brokered over the supervisor's gateway channel rather than through a policy egress rule, and a call from the sandbox to anywhere else is blocked at the boundary.
The headline: the same agent image, deployed unchanged, gets its model access brokered by the gateway and network-egress governance for free. Its model calls resolve through https://inference.local/v1; a direct call to anywhere else is blocked at the sandbox boundary.
The full worked runbook with narration beats lives in the notebook at plugins/nemo-deployments/examples/openshell/DEMO.ipynb. The already-correct demo agent config lives at plugins/nemo-deployments/examples/openshell/agent/config.yaml, and a readable reference for the policy the backend generates (plus an override example) lives at plugins/nemo-deployments/examples/openshell/local-sandbox-policy.yaml. This skill is the concrete command path; read those files for context and overrides.
When to use
The user has a built (or buildable) NAT agent and wants it deployed under sandbox isolation with a governed default-deny network policy.
The user explicitly asks for the openshell-local executor, a SandboxPolicy, or Landlock/egress governance.
If the agent image does not exist yet, run nemo-build-agent first to scaffold and validate the NAT workflow, then return here to deploy it as a sandbox. This skill does not author agent YAML.
Pre-flight
Verify these prerequisites before touching the deploy steps. Do not improvise around a missing one; stop and tell the user what is not running.
Commands below assume nemo and openshell are on your PATH. In a repo checkout they live in the workspace venv, so prefix with .venv/bin/ (e.g. .venv/bin/openshell, .venv/bin/nemo).
OpenShell gateway reachable on :17670, with its JWT signing keys generated.:17670 is OpenShell's documented docker default. It must NOT be : that
belongs to the NeMo platform (the gateway container image and the CLI's example both steer onto , the collision
trap). Docker-driver sandboxes REQUIRE the gateway to mint sandbox JWTs, so you must
generate the signing keys once before the gateway starts (see 's
and the header). Run the
one-time key generation, then bring the compose stack up and register it:
:8080
openshell gateway add http://127.0.0.1:8080
:8080
gateway.toml
[openshell.gateway.gateway_jwt]
docker-compose.yml
# one-time: generate the JWT signing keys the docker driver needs to mint# sandbox tokens (writes /var/lib/openshell/tls/jwt/*). Re-run only if the# /var/lib/openshell state dir is wiped.
docker run --rm --user 0 -v /var/lib/openshell:/var/lib/openshell \
ghcr.io/nvidia/openshell/gateway:0.0.92 generate-certs \
--output-dir /var/lib/openshell/tls \
--server-san 127.0.0.1 --server-san localhost --server-san host.openshell.internal
docker compose -f plugins/nemo-deployments/examples/openshell/docker-compose.yml up -d
openshell gateway add http://127.0.0.1:17670 --local --name docker-dev
Confirm the CLI reaches the gateway and the endpoint column reads :17670, not :8080:
openshell gateway list # * docker-dev http://127.0.0.1:17670 ... plaintext
openshell sandbox list # reaches the gateway (e.g. "No sandboxes found.")
Tear the gateway down after the demo with docker compose -f plugins/nemo-deployments/examples/openshell/docker-compose.yml down.
NeMo Platform up, listening on all interfaces, started with the executor config. The
openshell-local executor lives in packages/nmp_platform/config/local.yaml,
which is NOT the config nemo services run loads by default (that bundled default
has no deployments: openshell executor), so it must be passed with --config.
Start (or restart) it as:
If the platform is down, route to nemo-setup. --host 0.0.0.0 matters: the
inference.local route is dialed from the sandbox, not from the gateway process. The
docker driver writes a literal 172.18.0.1 host.openshell.internal into each
sandbox's /etc/hosts (the sandbox network's gateway address), so the platform has
to be listening there. On --host 127.0.0.1 every model call fails with a 503. It
also exposes an unauthenticated dev platform on every interface, LAN included, so do
not run this on an untrusted network. If the platform is up but was started
without --config, the executor is absent and Step 4 fails with an unknown-executor
error; restart with the --config flag above. The executor block that ships in that
file:
deployments:executors:-name:local-docker# ordinary docker deployments (the default)backend:dockerconfig: { pull_images:false, port_range_start:9000, port_range_end:9100 }
-name:openshell-localbackend:openshellconfig:gateway_endpoint:http://127.0.0.1:17670serve_workdir:/home/sandbox# sandbox-writable CWD for `nat serve`platform_egress:null# agent uses inference.local (gateway-managed),# so the sandbox needs NO direct egress -># a pure default-deny SandboxPolicydefault_executor:local-docker# sandbox is opt-in; Step 4 names the executor
platform_egress: null is the shipped default and yields a policy with no egress
rules at all. See the Alternate branch at the end if you deliberately want the older
direct-egress path.
Packaging and backend dependencies present. Step 2 (nemo agents package) needs
python-on-whales (the agents plugin container extra), and the OpenShell backend
needs the openshell SDK (the deployments plugin ships it in its openshell extra):
If DEPS_MISSING, install the backend extra: uv sync --package nemo-deployments-plugin --extra openshell. Base make bootstrap-python does not
install the platform-restricted openshell wheel, so it needs this step. The
packaging dependencies ship with nemo-agents-plugin itself and need nothing extra.
Step 1: Pick a model and wire the inference.local route
The agent reaches models through OpenShell's gateway-managed inference.local route: the gateway routes https://inference.local/v1 to a registered provider (the platform Inference Gateway) and injects the real credential, so the sandbox needs no direct egress. First pick a model the Inference Gateway serves, then do the one-time operator wiring on the gateway.
nemo models list --all-pages # pick a model the gateway serves; it paginates, so --all-pages
MODEL='default/openai-openai-gpt-4o-mini'# example only; set to a model the list above shows
model_name MUST be a model that actually exists on this platform's Inference Gateway. A model the gateway cannot resolve makes nat serve exit inside the sandbox, which the reconciler reports as FAILED with the serve log tail rather than a READY deployment that 502s. Prefer a gpt-4o-mini-class model for clean ReAct tool-calling; avoid verbose reasoning models that emit empty content.
Register the platform Inference Gateway as an openshell provider and bind inference.local to it (once per gateway). host.openshell.internal is the gateway's alias for its own host, where the platform listens. The credential is a dummy: the gateway injects the real one.
openshell provider create --name nemo-igw --type openai \
--credential OPENAI_API_KEY=empty \
--config OPENAI_BASE_URL=http://host.openshell.internal:8080/apis/inference-gateway/v2/workspaces/default/openai/-/v1 \
|| echo"(provider may already exist; use 'openshell provider update' to change its config)"
openshell inference set --provider nemo-igw --model "$MODEL"
openshell inference get # verifies the route gateway-side
inference set verifies the endpoint gateway-side, so a clean inference get is your confirmation the route is live before you deploy.
Step 2: Package the agent as a sandbox image
Use the checked-in demo config plugins/nemo-deployments/examples/openshell/agent/config.yaml. It is a normal NAT ReAct config that is already sandbox-ready: its LLM points at https://inference.local/v1, the general.telemetry / nemo_files tracer block is removed, and the model id is left as a deploy-time param. Its agent/ folder holds only config.yaml, so it is a clean Docker build context.
Two properties of this config are mandatory for the sandbox path, so preserve them if you start from your own agent instead:
LLM points at inference.local.base_url: https://inference.local/v1, and api_key is a non-empty placeholder (not-used): it MUST be non-empty because the gateway swaps in the real credential, but an empty string makes NAT reject the config.
No general.telemetry / nemo_files block. The stock react-agent.yml example enables the nemo_files tracing plugin, which is NOT installed in the packaged sandbox image, so nat serve rejects the config and exits, and the deployment lands in FAILED with the config error in its status message. Remove the whole general.telemetry block before packaging. (The demo config already has it removed.)
The wiki tool is registered in the demo config but its egress to Wikipedia is blocked under the zero-egress policy, so only the current_datetime path is exercised below. Trim the wiki tool from tool_names/functions if you want no dead tools.
If you start from your own agent, copy it into its own clean directory named config.yaml and edit the copy (not the repo file):
mkdir -p /tmp/igw-agent
cp <your-agent>.yml /tmp/igw-agent/config.yaml
# then: set base_url: https://inference.local/v1, keep api_key non-empty,# remove the general.telemetry block, leave model_name as ${NEMO_DEFAULT_MODEL}
The clean directory and the config.yaml name both matter (verified the hard way): nemo agents package uses the agent file's parent directory as the Docker build context, so a shared dir like bare /tmp can hold a file that breaks docker buildx (failed to unmarshal ... invalid UTF-8); and it bakes the file into the image at /workspace/<basename>, so naming it config.yaml makes it land at /workspace/config.yaml, the exact path Step 3's serve command loads. On a name mismatch nat serve never finds its config and exits, and the deployment reports FAILED with that error rather than serving.
Build the image with the OpenShell runtime profile (adds the sandbox user and required packages). Use the shipped demo config:
The config is baked into the image at /workspace/config.yaml, which is exactly what Step 3's serve command loads. The model id is injected at deploy time via nat serve --override llms.llm.model_name <MODEL> (Step 3), so the unset ${NEMO_DEFAULT_MODEL} in the baked config is fine.
Verification: docker image inspect nemo-agent-igw:test >/dev/null 2>&1 && echo IMAGE_OK || echo IMAGE_MISSING. If IMAGE_MISSING, the build failed; surface the nemo agents package output and stop.
Step 3: Create the DeploymentConfig
Describe the container: the image, the nat serve command the backend runs inside the sandbox (with the model injected via --override), and the port. The agent reaches the LLM through inference.local, so there is no proxy handling or egress plumbing here.
$MODEL here MUST be the same id you passed to openshell inference set in Step 1, so the model the agent requests matches the route the gateway forces.
Step 4: Deploy (executor = openshell-local)
Sandbox is opt-in: name the executor explicitly ("executor": "openshell-local"). The default executor is local-docker, so ordinary deployments and the e2e harness keep their normal docker/k8s path.
Behind the scenes the OpenShellDeploymentBackend generates a pure default-deny SandboxPolicy (read-only /opt for the interpreter; read-write /home/sandbox, /tmp, /dev/shm for the Dask runtime nat serve spins up; run_as_user: sandbox; and, because platform_egress is null, no network egress rules at all), creates the sandbox from the image and applies the policy, runs the serve command in the sandbox-writable serve_workdir (/home/sandbox), and exposes the service through the gateway. The agent's model calls leave the sandbox only through the gateway-routed inference.local path.
Step 5: Wait for READY and read the endpoint
The reconciler drives PENDING -> STARTING -> READY, typically well under a minute.
for i in $(seq 1 30); do
status=$(curl -sf "$BASE/deployments/igw-agent" | jq -r '.status')
echo"$status"
[ "$status" = "READY" ] && break
[ "$status" = "FAILED" ] && { echo"DEPLOY_FAILED"; break; }
sleep 3
done
URL=$(curl -sf "$BASE/deployments/igw-agent" | jq -r '.endpoints[0].url')
echo"$URL"# e.g. http://<sandbox>--<svc>.openshell.localhost:17670/
If the status reaches FAILED or never leaves PENDING/STARTING, jump to the recovery table below. Do not proceed to invoke until READY. READY gates on the sandbox being up, the serve launcher exiting cleanly, the serve process still being alive on the poll, and nat serve answering a reachability probe on its port, so the endpoint is serving as soon as it reports READY. A serve process that exits (bad config, unresolvable model) flips the deployment to FAILED on the next poll, with the tail of its log in the status message.
Step 6: Invoke the agent
Ask a question that forces both a tool call and an LLM call. The agent's LLM call goes to inference.local, which the gateway routes to the platform Inference Gateway, so the sandbox makes no direct egress.
curl -sf -X POST "${URL}generate" -H 'content-type: application/json' \
-d '{"input_message":"What is the current date and time? Use your current_datetime tool"}' | jq .
# -> {"value":"The current date and time is 2026-... +0000."}
Other routes the served workflow exposes: POST /v1/chat/completions, /chat, /v1/workflow, and /generate/stream.
Verification: the response must contain a non-empty value. A 502 Service endpoint is not reachable means nat serve (port 9000) is not answering. Read the serve log inside the sandbox:
The most common root causes are: the MODEL is not served on your Inference Gateway (nemo models list --all-pages), the config did not bake to /workspace/config.yaml, or a leftover general.telemetry block made NAT reject the config. An empty or error value means the LLM call failed at the gateway or the model misbehaved. Either way, check the recovery table.
Step 7: Prove the sandbox has zero direct egress
The security punchline. Show the sandbox can reach nothing on the network directly:
# the sandbox name is nmp-<hash>; derive it from the endpoint URL (or read `openshell sandbox list`)
SBX=$(curl -sf "$BASE/deployments/igw-agent" | jq -r '.endpoints[0].url' | sed -E 's#^https?://##; s#--.*##')
openshell sandbox exec --name "$SBX" -- curl -sS -m 5 https://example.com # BLOCKED (policy default-deny)# a NONZERO exit from the inner curl is the PASS# meanwhile Step 6's LLM call still worked: it went via inference.local (gateway-routed, not sandbox egress)
Step 8: Clean up
curl -sf -X DELETE "$BASE/deployments/igw-agent"# tears down the sandbox
curl -sf -X DELETE "$BASE/deployment-configs/igw-agent-cfg"
Tear down the gateway too when you are done:
docker compose -f plugins/nemo-deployments/examples/openshell/docker-compose.yml down
Gotchas (all verified against a live gateway)
The inference.local route must be wired before invoke. The agent hits https://inference.local/v1; if you never ran openshell provider create + openshell inference set (Step 1), the gateway has no route and nat serve's model calls fail. openshell inference get should show the nemo-igw provider and your model.
Remove general.telemetry / nemo_files before packaging. The stock react-agent.yml enables the nemo_files tracer, which is not installed in the sandbox image, so nat serve rejects the config and the deployment goes FAILED. The shipped agent/config.yaml already removes it.
Keep api_key non-empty.base_url: https://inference.local/v1 with an empty api_key makes NAT reject the config. Use a placeholder like not-used; the gateway injects the real credential.
Serve workdir must be sandbox-writable. The image owns /workspace as its agent user, which the sandbox user cannot write. serve_workdir is /home/sandbox; the policy grants read-write on /home/sandbox, /tmp, and /dev/shm (Dask needs POSIX semaphores under /dev/shm).
Model choice matters for ReAct, and the model must exist on the Inference Gateway. Use a model_name your nemo models list --all-pages actually shows; switchyard names drift between platforms and a missing one makes nat serve exit (endpoint 502). A gpt-4o-mini-class model gives clean tool-calling; verbose reasoning models can emit empty content that breaks the ReAct loop.
The wiki_search tool cannot reach Wikipedia under the zero-egress policy. It stays registered in the demo config, but its external egress is blocked, so only the current_datetime path is exercised. Trim wiki from tool_names/functions if you want no dead tools.
Platform must bind 0.0.0.0. The inference.local route is dialed from the sandbox, not from the gateway process: the docker driver writes a literal 172.18.0.1 host.openshell.internal into each sandbox's /etc/hosts (the sandbox network's gateway address), so the platform has to be listening there. On --host 127.0.0.1 every model call fails with a 503. 0.0.0.0 puts an unauthenticated dev platform on your LAN; do not do it on untrusted wifi.
openshell inference set validates from the host, not from the sandbox. It prints Validated Endpoints whenever the CLI or gateway can reach the URL, which is true even for a loopback-only platform. A green validation followed by a 503 at invoke is exactly that case: the route is fine, the platform is not reachable at the sandbox network's gateway address.
Docker sandboxes need gateway-minted JWTs. If the gateway logs complain about missing signing keys, run the one-time generate-certs command in Pre-flight step 1 before docker compose up.
sandbox exec rejects newlines in args. To push a file into a sandbox by hand, base64-encode it (echo <b64> | base64 -d > f) or use sandbox create --upload <file>.
Endpoint host is docker-driver specific. The exposed *.openshell.localhost:17670 URL and the sandbox's host.openshell.internal hop to the platform both assume the docker driver.
If verification fails
Symptom
Cause
Recovery
openshell gateway list / sandbox list cannot reach the gateway
Gateway not running
Start the docker-driver gateway (Pre-flight step 1: generate-certs once, then docker compose up -d); re-check
Gateway logs about missing JWT signing keys
generate-certs never run
Run the one-time generate-certs command (Pre-flight step 1), then restart the gateway
health/ready not ready
Platform down
Route to nemo-setup, return when ready
Deploy FAILED with an unknown/unregistered executor error
Platform started without the executor config
Restart with nemo services run --host 0.0.0.0 --port 8080 --config packages/nmp_platform/config/local.yaml (the bundled default config has no openshell executor)
openshell gateway list shows the endpoint on :8080
Gateway collides with the platform port
Recreate the gateway on :17670 (docker driver, plaintext) per Pre-flight step 1; :8080 belongs to the platform
Deploy stuck PENDING/STARTING
Image missing sandbox user, or serve command wrong
openshell sandbox list; inspect the sandbox; confirm Step 2 used --sandbox-runtime openshell
Deploy FAILED
Policy or gateway rejected the sandbox, the serve launcher exited non-zero, or the serve process died after launch
Check platform logs (nemo services logs -n 100) and the deployments reconciler output; the FAILED status message carries the launcher exit detail or the serve log tail. nemo deployments logs <name> returns the workload's own log
Invoke returns 502 Service endpoint is not reachable
The deployment is not READY, or nat serve died after coming up
Wait for READY before invoking; if a READY deployment still 502s, read the serve log (nemo deployments logs <name>, or openshell sandbox exec --name <nmp-hash> -- cat /tmp/nemo-serve.log). A bad config path, a leftover general.telemetry block, or an unresolvable model_name surfaces as FAILED, not a 502
Invoke returns 503 inference service unavailable (in the response or the serve log)
The inference.local route resolved, but the gateway's upstream hop to the platform failed
Almost always a platform bound to 127.0.0.1; restart it with --host 0.0.0.0. Confirm the address the sandbox actually dials with openshell sandbox exec --name <nmp-hash> -- cat /etc/hosts (look for host.openshell.internal) and check the platform answers there (curl -sf http://<that-ip>:8080/health/ready). A clean openshell inference set does NOT rule this out: it validates from the host
Invoke returns empty/error value, or serve log shows connection refused to inference.local
inference.local route not wired, or model misbehaved
Confirm openshell inference get shows the nemo-igw provider + your model; re-run Step 1's provider create / inference set; try a gpt-4o-mini-class model
example.com reachable in Step 7
Egress policy not applied
Confirm executor is openshell-local and the generated default-deny policy is attached to the sandbox
The shipped design routes model traffic through inference.local and grants the sandbox no direct egress. If you deliberately want the older direct-egress path instead (the agent calls the Inference Gateway itself at host.docker.internal:8080), you must editpackages/nmp_platform/config/local.yaml to set platform_egress on the executor (it is NOT the shipped default):
config:gateway_endpoint:http://127.0.0.1:17670serve_workdir:/home/sandboxplatform_egress:host:host.docker.internalport:8080binaries: [/workspace/.venv/bin/python3.13] # the venv python opens the socket, NOT curl
Then the sandbox's generated policy has a single egress rule to the Inference Gateway. In this branch you also skip Step 1's inference.local wiring and instead point the agent config's base_url directly at the Inference Gateway: http://host.docker.internal:8080/apis/inference-gateway/v2/workspaces/default/openai/-/v1. Note: the connecting binary must be on the egress allowlist (the venv/uv python that makes the LLM call, not curl); a hand-written override that only lists curl silently blocks nat. Restart the platform with --config after editing so the change takes effect.
Related skills
nemo-build-agent: scaffold, validate, and build the NAT agent image before deploying it here.
nemo-try-agent: query an already-deployed agent.
nemo-status: read-only health dashboard for platform, agents, providers, and models.
inference: register providers and virtual models the agent's Inference Gateway model name resolves to.
Known limitations
The NAT config is baked into the image; deploy-time config injection (config_files) is a follow-up.
inference.local requires the one-time operator wiring (provider + inference set) per gateway; the deployment backend does not auto-register it yet.
The exposed endpoint host and the sandbox's host.openshell.internal hop to the platform are docker-driver specific.
The verified end-to-end flow (agent packaged, deployed through openshell-local to READY, invoke returning a real value via inference.local, direct egress to example.com blocked) depends on the openshell-local executor wiring landing in your platform config (loaded via --config) and the inference.local route being wired on the gateway.
