edgegate-runner 0.1.7

EdgeGate self-hosted Behavioral-Gate device runner — runs the gate on a connected Snapdragon device and posts a signed verdict.

edgegate-runner

Connect your edge device to EdgeGate — regression gates and a live device registry for on-device AI.

Works on any Linux/macOS box with Python 3.10+: NVIDIA Jetson, Snapdragon-connected hosts, Raspberry Pi, industrial gateways, laptops.

Install

pip install edgegate-runner

Connect a device (60 seconds)

1. In your EdgeGate workspace: Settings → API Keys → Create key (needs Pro tier). Copy the egk_… token.
2. On the device:

export EDGEGATE_TOKEN=egk_...                 # your workspace API key
export EDGEGATE_WORKSPACE_ID=<workspace-uuid> # shown in the dashboard URL / settings

edgegate-runner agent --vendor nvidia --silicon orin-nano-8gb --name my-jetson

The device appears in your workspace dashboard under Device Targets within seconds, with a live/offline badge driven by its 30-second heartbeat. Stop the agent and the badge flips to offline within ~90s.

--vendor is free-form (qualcomm, nvidia, intel, …); --name defaults to the hostname. Add --once for a smoke test that sends a single heartbeat and exits.

Run it as a service (recommended)

# /etc/systemd/system/edgegate-agent.service
[Unit]
Description=EdgeGate device agent (liveness heartbeat)
After=network-online.target
Wants=network-online.target

[Service]
User=<your-user>
EnvironmentFile=/etc/edgegate-agent.env   # EDGEGATE_TOKEN=... EDGEGATE_WORKSPACE_ID=...
ExecStart=/usr/local/bin/edgegate-runner agent --vendor nvidia --name my-jetson
Restart=always
RestartSec=10

[Install]
WantedBy=multi-user.target

sudo systemctl enable --now edgegate-agent

Behavioral Gate on NVIDIA Jetson (llama.cpp)

With pip install llama-cpp-python on the box, the runner executes Behavioral-Gate runs against a GGUF model (vendor nvidia) — same eval sets, same scoring, same signed verdict format as Snapdragon runs. Works online (edgegate-runner run) and air-gapped (edgegate-runner offline).

Behavioral-Gate runs (Snapdragon hosts)

On a host with a Snapdragon device attached via adb, the runner also executes EdgeGate Behavioral-Gate runs — pulling the run config and model bundle, running the gate on-device, and posting back a summary-only signed verdict (raw model output never leaves your box):

edgegate-runner run --run-id <run-id>

Air-gapped? edgegate-runner offline --config config.json runs entirely from local files.

Configuration

Env var	Meaning	Default
EDGEGATE_TOKEN	Workspace API key (required)	—
EDGEGATE_WORKSPACE_ID	Workspace UUID (required)	—
EDGEGATE_API_URL	EdgeGate API base URL	https://edgegateapi.frozo.ai

Docs: https://edgegate.frozo.ai/docs · © EdgeGate. Powered by Qualcomm AI Hub.