Command-line reference#

This reference is generated from the installed commands in each top-level sample’s pyproject.toml under agent-samples/ and model-server-samples/, and the literal argparse declarations in its entry-point module. Worker and service commands are launcher-managed process protocols, so they are intentionally excluded from the user-facing catalog.

lab_instrument_monitoring#

Launch lab instrument monitoring with reused model dependencies.

Run from agent-samples/lab-instrument-monitoring/:

$ uv run lab_instrument_monitoring [--expose-web-events]

Options

--expose-web-events

bind the unauthenticated event viewer to all IPv4 interfaces instead of loopback

simple_vlm_example#

simple-vlm-example orchestrator — vision Q&A over voice or text.

Run from agent-samples/simple-vlm-example/:

$ uv run simple_vlm_example [--capture]

Options

--capture

record participant video, bidirectional audio, and data-channel traffic

tea_making_sample#

Launch native tea guidance with reused model services.

Run from agent-samples/tea-making-sample/:

$ uv run tea_making_sample [--expose-web-events]

Options

--expose-web-events

bind the unauthenticated event viewer to all IPv4 interfaces instead of loopback

xr_render_demo#

xr-render-demo orchestrator. Runs the process stack for this sample.

Run from agent-samples/xr-render-demo/:

$ uv run xr_render_demo [--capture]

Options

--capture

record participant video, bidirectional audio, and data-channel traffic

model_servers#

model-servers orchestrator — starts one shared AI inference stack and exits.

Run from model-server-samples/model-servers/:

$ uv run model_servers [--stop] [--models NAME_OR_PATH] [--allow-anonymous] [--gpu-profile NAME]

Options

--stop

Stop every persisted model-server stack and exit.

--models NAME_OR_PATH

Deployment profile to start: a shipped name (default, vlm_llm_nim) or a path to a profile JSON.

--allow-anonymous

Start without HF_TOKEN (unauthenticated downloads of the multi-GB checkpoints may stall indefinitely).

--gpu-profile NAME

Use a named YAML GPU profile instead of automatic detection. Intended for explicitly reviewed custom hardware profiles.