inspect-robots-dropbear

An Inspect Robots policy adapter for Dropbear-hosted DreamZero-YAM. Discovery and construction are offline; the first trial reset opens one lazy Dropbear connection, and later trials reuse that connection while starting fresh logical episodes.

Licensed under Apache 2.0. It supports Python 3.11 through 3.14 and requires the immutable dropbear[dreamzero]==0.1.0a10 SDK release.

Using it against a Dropbear-hosted model needs an API key and an entitlement for that model; the adapter itself is open.

Worked examples live in examples/: a complete evaluation and a skeleton embodiment showing the observation and action contract.

Install and discover

uv add inspect-robots-dropbear

Confirm the expected Dropbear SDK is active before starting an evaluation:

python -c 'import dropbear; assert dropbear.__version__ == "0.1.0a10"'

Verify that the entry point is available without opening a cloud session:

inspect-robots list policies

The output must contain dropbear. Keep your existing registered task and embodiment; do not replace or rename either. Change only the policy selection in your existing evaluation command:

--policy dropbear -P model=dreamzero-yam

The default is YAM's qualified async_latest mode. Use sampling=async_8 for the explicit compatibility/rollback path and sampling=upstream_eval only for an open-loop dataset evaluation. The server keeps inference single-flight and latest-only. The SDK preserves two committed steps and applies its fixed absolute-target motion smoother only to the aligned async_latest suffix; the adapter exposes no custom buffering, horizon, or smoothing knobs.

DreamZero-YAM is qualified at exactly 30 Hz. -P control_hz=30 is accepted for explicitness; every other value fails during policy construction, before a paid session is opened. The model's 30 Hz action/data timebase is distinct from inference frequency and the robot driver's internal servo loop. Dynamic cadence must not be advertised until observation production, temporal admission, inference, and action execution consume one resolved rate end to end.

-P keep_warm_s=<seconds> holds the session after close (0-3600, default 0) so the next run reclaims it instead of starting cold -- 147s against 23s, measured back to back. A hold is billed at the full rate and close() no longer stops the meter, because parking keeps the GPU reserved for you. Use it while iterating; leave it at 0 for unattended runs.

Nothing enforces this rate. Inspect's rollout adds no wall-clock pacing, so the real rate is however fast your embodiment's step() returns; control_hz is what the action scheduler plans against. Pace the embodiment at 30 Hz. The adapter measures the gap between policy steps, records it as step_interval_ms in the sidecar, and warns once if the measured rate diverges from 30 Hz by more than 25%.

The first connection has a 1,800-second startup budget by default so DreamZero-YAM can finish loading and warmup. Set -P startup_timeout_s=<seconds> to another finite positive value when a target needs a different startup budget. This does not change timeout_s, the existing per-step action deadline, which remains 60 seconds by default.

Observation and simulator contract

The existing task and embodiment must provide all of the following on every policy step:

• top_cam, left_cam, and right_cam uint8 images, each with its own real Unix-epoch capture time in seconds (not a process-monotonic clock and not one synthetic shared time);
• finite packed joint_pos state with shape (14,) in YAM left-arm, left-gripper, right-arm, right-gripper order; and
• Inspect's integer extra["env_step"], starting at zero and advancing once per delivered action.

The adapter declares a 14-dimensional raw absolute-joint action at the commanded rate. It returns exactly one action per Inspect act() call while Dropbear owns DreamZero's managed action buffering. Simulator compatibility means matching those camera, state, action, clock, and rate contracts; it does not by itself establish physics parity, task success, or physical-robot safety.

Artifact ownership and joining

Inspect remains canonical for the EvalLog, aggregate scores, post-approval commanded-action JSONL, stored frames, Rerun recording, operator judgement, and trial termination/error state. The adapter adds one atomic diagnostics sidecar and records its relative path at TrialRecord.metadata["dropbear_telemetry"]:

dropbear/<run_id>/<sanitized-scene-id>-e<epoch>.jsonl

Schema-v2 sidecar rows contain package versions, session and serving identity, timestamp source, commanded cadence, model/hold action source, source control tick, source camera capture-to-execution age, timing, accurate maximum overlapping-target revision, chunk/merge disposition, and the same Inspect environment step. Join them to the EvalLog, action JSONL, or Rerun timeline using env_step; use join_key (<cache_generation>:<logical_action_index>) for Dropbear chunk diagnostics. Sidecars do not duplicate action vectors, images, credentials, authorization material, certificates, or endpoints.

Deterministic cleanup

Evaluation owners must call policy.close() in finally after the run, even when Inspect reports an error or cancellation. close() is synchronous and idempotent, and policy.session_id remains readable after close so the caller can verify that the exact session is gone:

dropbear sessions list

Do not stop unrelated sessions. The adapter also registers a bounded process-exit fallback, but it is not a substitute for explicit close.

Physical YAM boundary

This integration does not authorize an unattended physical run. For any physical YAM test, you own and must supply the embodiment package for your arm, validated limits, an attended operator gate, a working e-stop, and a rehearsed termination procedure. This adapter calls neither the embodiment nor hardware directly, and compatibility or serving evidence must not be reported as physical safety or effectiveness evidence.