Your control loop

Use the deployment from the quickstart. Map real sensor arrays to its inspected input names, shapes and dtypes. Checkpoint documentation defines camera placement, state units and action channel order. Pass your capture and actuator callbacks to this bounded loop:

live_episode.py

import servo

sv = servo.Servo()
deployment = sv.deployments.get(input("Deployment ID: "))
policy = deployment.policy()


def run_live_episode(capture_named_inputs, apply_with_safety_limits):
    with sv.session(
        policy, instruction="pick up the red cap and place it in the black box"
    ) as session:
        for _ in range(30):
            inputs = capture_named_inputs()
            chunk = session.predict(inputs=inputs)
            for action in chunk.actions:
                apply_with_safety_limits(action)

capture_named_inputs returns fresh NumPy arrays. apply_with_safety_limits enforces your hardware limits and paces each action according to the checkpoint’s control rate. Call run_live_episode with your own implementations; Servo provides neither hardware callback.

Strategy	Tradeoff
Execute the full chunk	Fewer requests; waits for a prediction between chunks
Execute fewer rows, then predict again	Fresher observations; more inference requests

Keep the hardware stop available. Inspect action units and ordering before moving. The example requests thirty chunks; your callback determines the duration. A session reuses its connection. Closing it does not stop the deployment. See local recovery for controlled handback after interrupted execution.

Get started

Guides

Reference

Your control loop