Local Healthcare Agent on DGX Station | DGX Station

View All Playbooks

View All Playbooks

Local Healthcare Agent on DGX Station

60 MIN

Run healthcare AI agents that analyze patient data and predict protein structures in an OpenShell sandbox on DGX Station

AI Agent DGX Station FHIR GB300 Healthcare NemoClaw Nemotron OpenFold3 OpenShell

Overview Instructions Troubleshooting

Docker and infrastructure

Symptom	Cause	Fix
`make up` hangs on model pull	Nemotron-3-Super is ~86 GB and takes 15–25 min on first download (longer on slow links)	Wait. Check progress with `docker compose logs -f ollama`. If interrupted, re-run — it resumes where it left off.
`OpenFold3: ✗ down` in `make status`	OpenFold3 takes ~3 minutes to load model weights on startup	Wait and re-run `make status`. Check logs with `docker compose logs -f openfold3`.
`failed to bind host port for 0.0.0.0:11434` on `docker compose up ollama`	Host Ollama is already listening on 11434 (common after the NemoClaw playbook)	Stop host Ollama: `sudo systemctl stop ollama && sudo systemctl disable ollama`. Or override in `.env`: `OLLAMA_PORT=11435` — `make setup` and `setup_sandbox.sh` source `.env` and configure the sandbox provider against the new port.
`unauthorized: <html><head><title>401 Authorization Required` when pulling `nvcr.io/nim/openfold/openfold3`	Docker is not authenticated against NGC; `NGC_API_KEY` in `.env` is the runtime credential, not the pull credential	Run `make ngc-login` (reads `NGC_API_KEY` from `.env`). Manual equivalent: `echo "$NGC_API_KEY" \| docker login nvcr.io -u '$oauthtoken' --password-stdin`.
OpenFold3 crashes with `device >= 0 && device < num_gpus INTERNAL ASSERT FAILED`	OpenFold3's PyTorch backend rejects multi-GPU containers; `count: all` exposes both GPUs on a dual-GPU station	`docker-compose.yml` pins to `LLM_GPU`/`OPENFOLD_GPU` (default `0`). On dual-GPU stations, set both to the GB300 index in `.env` and `docker compose up -d --force-recreate openfold3`.
`NGC_API_KEY not set` error	`.env` file missing or NGC key not configured	Run `cp .env.example .env` and edit to add your NGC API key from ngc.nvidia.com.
`exec format error` when pulling containers	Container architecture mismatch (x86 container on ARM64)	Ensure you're using ARM64-compatible containers. OpenFold3 (v1.3.0+) and Ollama support ARM64. Check with `docker inspect --format '{{.Architecture}}' <image>`.
Sandbox policy validation fails on startup	`landlock: hard_requirement` aborts if filesystem paths can't be enforced	Check that all paths in `sandbox-policy.yaml` exist on the system. If running on non-standard DGX OS, try `compatibility: best_effort` temporarily to diagnose.
`node: command not found` or OpenShell rejects v18	DGX Station ships with Node.js v18.19.1; OpenShell/OpenClaw need v22+	`curl -fsSL https://deb.nodesource.com/setup_22.x \| sudo -E bash - && sudo apt-get install -y nodejs`. `make prereq` validates the version automatically.

Gateway and sandbox

Symptom	Cause	Fix
Gateway fails with "ContainerManager" error	DGX Station uses cgroup v2 and needs the systemd driver flag	Start gateway with: `OPENSHELL_K3S_ARGS='--kubelet-arg=cgroup-driver=systemd' openshell gateway start`
`openshell status` returns "Connection reset by peer" right after `gateway start`	k3s inside the gateway container takes 10–15s to accept connections	Wait. Use the polling loop from `instructions.md` Step 4: `for i in $(seq 1 30); do openshell status 2>/dev/null \| grep -q Connected && break; sleep 2; done`.
`openshell status` shows "Not Connected" after 30s	Gateway not started or crashed	Run `openshell gateway start` (with the cgroup flag above). Check `docker ps` for the gateway container.
`openshell sandbox create` fails with "port already forwarded" or hangs on `--forward 18789`	Stale port forward from a previously deleted sandbox is still registered	List forwards: `openshell forward list`. Stop each one bound to `:18789`: `openshell forward stop 18789 <sandbox-name>`. `setup_sandbox.sh` does this automatically before re-creating the sandbox.
Existing OpenShell gateway from another playbook silently reused with new name	`openshell gateway start` resumes any existing gateway in stopped state	Acceptable, but to start clean: `openshell gateway destroy` before running `openshell gateway start`.
Port 18789 not accessible remotely	SSH tunnel not active or port forward dead inside sandbox	Check with `openshell forward list`. If dead: `openshell forward stop 18789 clinical-sandbox && openshell forward start -d 18789 clinical-sandbox`. Then re-establish SSH tunnel from your machine.
`requests` library doesn't work in sandbox	Sandbox Python uses curl subprocess for HTTP, not the requests library	This is by design. All HTTP calls in agent scripts must use `subprocess.run(["curl", ...])` and `json.loads()`. The `fhir_helpers.py` library handles this automatically.

Inference and model

Symptom	Cause	Fix
Agent returns empty response or timeout	Model unloaded from GPU memory after idle timeout	Send a warmup message first. Check `OLLAMA_KEEP_ALIVE` is set to `4h` in docker-compose.yml.
`curl: (7) Failed to connect` to inference.local	OpenShell inference provider not configured or Ollama not running	Verify Ollama: `curl -sf http://localhost:${OLLAMA_PORT:-11434}/`. Re-run `make setup` — it configures the inference provider automatically.
Sandbox cannot reach host Ollama (only Docker bridge IP times out)	Host Ollama's systemd unit binds to `127.0.0.1` by default	Add a systemd override binding to all interfaces: `sudo systemctl edit ollama` and insert `[Service]` then `Environment="OLLAMA_HOST=0.0.0.0"`, then `sudo systemctl daemon-reload && sudo systemctl restart ollama`. Docker Ollama (the default in this playbook) already binds to `0.0.0.0`.
OpenFold3 returns error for molecular visualization	Protein sequence too long or malformed input	OpenFold3 supports sequences up to 4096 amino acids (PyTorch backend) or 2048 (TensorRT). Check the protein sequence in `build_viewer.py`'s drug-target table.

Agent and skills

Symptom	Cause	Fix
`make setup` fails	Setup did not complete successfully	Re-run `make setup` — the script recreates the sandbox from scratch with fresh config. Ensure you're on OpenShell >= 0.0.33.
`make check` shows stale skills	Workspace skill copies don't match the repo after an update	The check output tells you which skills are stale. Re-run `make setup` or manually copy from `/sandbox/clinical-intelligence/skills/` to `~/.openclaw/workspace/skills/` inside the sandbox.
ENOENT errors for memory files in logs	OpenClaw tries to read daily memory files that don't exist	Create the memory directory: `mkdir -p ~/.openclaw/workspace/memory && touch ~/.openclaw/workspace/MEMORY.md` inside the sandbox. `make check` detects this.
Agent writes code from scratch instead of using helpers	Stale IDENTITY.md or analysis-methods skill in workspace	Run `make check` to verify. If stale, the workspace IDENTITY.md doesn't have the `fhir_helpers` import instruction.
Agent uses wrong LOINC code for eGFR	Agent used its own training knowledge instead of reading the skill file	Run `make check` to verify skills are synced. The fhir-basics skill lists `33914-3` for eGFR. If the workspace copy is stale, the model uses its own (often wrong) LOINC codes.

Demo and queries

Symptom	Cause	Fix
FHIR queries return 0 patients	Wrong SNOMED code format	Use bare codes: `code=44054006`, not `code=http://snomed.info/sct\|44054006`. The skill files contain the correct patterns.
Charts not visible in dashboard	Canvas directory not accessible or file not saved to correct path	Charts must be saved to `~/.openclaw/canvas/`. View canvas at `http://localhost:18789/__openclaw__/canvas/`.
`make test-full` fails on L4/L5 agent tests	Agent query timed out, FHIR server unreachable from sandbox, or Ollama model unloaded	Check step by step: (1) `make status` — are Ollama and OpenFold3 healthy? (2) `make check` — are skills and config synced? (3) Send a warmup message in the dashboard to reload the model. (4) Run `make test --level 3` first to isolate whether the issue is infrastructure, config, or agent-level.

Resources