| # Simulator integration interface |
|
|
| Each benchmark owns its simulator-facing protocol and adapter here. Each model |
| implements a policy under `AgentPolicies/<profile>/`. The shared Python types live in |
| [`benchkit/interfaces.py`](../../benchkit/interfaces.py) and |
| [`benchkit/contracts.py`](../../benchkit/contracts.py); do not create a different |
| copy of the policy API for each benchmark or provider. |
|
|
| For independent processes/nodes, use the [SIM server protocol](SERVER_PROTOCOL.md). |
| The native adapter is instantiated **inside** the benchmark server; the runner |
| holds `benchkit.sim_server.client.SimServerBenchmarkAdapter`. This retains the |
| typed interface below without sharing a simulator handle with policy code. |
|
|
| The supported product direction is **direct model control**, not hybrid control. |
| Do not add a VLA action proposer, learned fallback controller, autonomous task |
| skill service or hidden human correction between the model and simulator. |
|
|
| The interface standardizes the lifecycle, not robot capabilities. Camera sets, |
| state channels, action dimensions, coordinate frames, controllers and native |
| success conditions remain benchmark-specific. A model must declare compatibility |
| with those conditions instead of receiving an invisible task-solving wrapper. |
|
|
| ## Who implements what |
|
|
| | Owner | Interface or artifact | Responsibility | |
| | --- | --- | --- | |
| | Benchmark adapter (`bench_server/adapter.py` in RoboDojo) | `BenchmarkAdapter` | Expose the pinned descriptor, observation/action specifications, selected episodes and an episode-session factory. | |
| | `<benchmark>/server.py` | Independently launched SIM server | Host the native factory, declare runtime supplements and keep native control/scoring private. Shared transport mechanics live in `benchkit/sim_server/`. | |
| | Benchmark adapter or native worker | `EpisodeSession` | Reset, execute one native control target, return the transition, collect native metrics/artifacts and close resources. | |
| | Benchmark selection definition (`bench_server/protocol/task_catalog.json` in RoboDojo; `evaluation/plan.py` where implemented) | Selection plan | Declare the task/variant/state schedule and required runtime resources. Selection is independent of model identity and observed success. | |
| | `<benchmark>/EVALUATION_PROTOCOL.md` | Native track specification | Explain sensors, actions, horizons, task variants, native scoring, sampling and verified limitations. | |
| | `AgentPolicies/<profile>/` | `Policy` | Check compatibility, initialize episode memory, produce an action chunk or stop from each scheduled observation, and clear episode state. | |
| | `AgentPolicies/<profile>/` and `AgentPolicies/policy_support/` | Trusted driver and reusable decision loop | Connect to the service, execute bounded action prefixes and count calls/controls. | |
| | `benchkit/` | Record, source and report tools | Supply shared formats, frozen-source capture, audits and reports; retained campaign helpers support older workflows. | |
|
|
| RoboDojo's `bench_server/` groups its service adaptation, private worker client |
| and `protocol/` definitions. `environment/` contains the native runtime. See its |
| [directory guide](RoboDojo/README.md#directory-responsibilities). |
|
|
| Only the evaluator constructs an adapter or holds its session. The policy is not |
| given `reset`, `step`, `metrics`, simulator handles, task-state files or a scorer. |
| An in-process Python interface is an ownership boundary, not an OS sandbox. |
|
|
| ## Episode lifecycle |
|
|
| ```text |
| Frozen plan -> adapter.open_episode(EpisodeSpec) -> session.reset() |
| | |
| v |
| policy.act(permitted Observation) -> PolicyDecision |
| | |
| agent driver executes a bounded prefix |
| | |
| session.step(one native action) -> Transition |
| | |
| next scheduled observation, or native/budget end |
| | |
| native metrics + records + artifacts + cleanup |
| ``` |
|
|
| `EpisodeSpec` is evaluator-private. The runner builds the public |
| `EpisodeContext` for `Policy.start_episode`; never forward reset seeds or layout |
| metadata wholesale. `Policy.end_episode` clears method state. Optional |
| `ExecutionAwarePolicy.observe_execution` receives counter-only execution |
| feedback, not rewards or private simulator state. Optional |
| `ArtifactBoundEpisodeSession.bind_artifact_dir` gives the session a runner-owned |
| artifact directory before reset. |
|
|
| ## Observation and action rules |
|
|
| The adapter must explicitly construct an `Observation` from allowed fields. |
| Do not pass an upstream observation/info dictionary through unchanged: it may |
| contain object poses, segmentation, reward, success or reset information. |
| Document camera resolution/encoding and permitted state channels in the native |
| protocol; `ObservationSpec` is a compact declaration, not a complete data-leak |
| checker. The scoring side may retain richer evidence without exposing it to the |
| policy. |
|
|
| `ActionSpec` declares action dimension/order, bounds, frequency, frame, rotation |
| and gripper convention. An `ActionChunk` contains those native-contract vectors; |
| the agent-side runner executes at most the configured prefix before requesting another |
| decision. Invalid vectors are recorded as errors, not silently clipped or |
| repaired through another model request. |
|
|
| Protocol-fixed units, joint ordering, interpolation and the native low-level |
| controller belong to the adapter. Visual localization, grasp selection, motion |
| planning, model-specific IK and voluntary |
| give-up preferences belong to the model implementation and must respect the |
| declared interaction budget. Learned auxiliary policies and autonomous task |
| skill services are outside this repository's direct-control scope. |
| See [POLICY_PROTOCOL.md](POLICY_PROTOCOL.md). |
|
|
| ## Sampling, scoring and reports |
|
|
| Fast is a frozen subset with one attempt per selected case. Full is the verified |
| native task/variant/seed/episode schedule, including planned repetitions, not |
| retries selected after seeing a failure. RoboDojo declares a five-layout `fast` |
| panel and a 50-layout `full` panel for `classify_objects`, each once; neither |
| covers every RoboDojo task. Other full execution presets remain benchmark-specific; |
| document the actual supported schedule rather than adding an unsupported mode label. |
|
|
| The native evaluator decides success. Keep native partial score distinct from |
| boolean success, and keep unavailable scores null. Record the selected sample |
| denominator, completed/failed/error/unattempted cases, policy calls, executed |
| action decisions, native controls and physics ticks where available. A stop |
| response counts as a policy call but executes no action. Infrastructure checks |
| remain diagnostics even if their controls happen to trigger native success. |
|
|
| Reports must distinguish direct-control model implementations, observation/action |
| tracks, native versions and budgets. Hybrid results from external reports are |
| not direct-control baselines for this repository. |
| Do not pool different benchmarks' raw scores or treat an external leaderboard |
| snapshot as a paired rerun. Store report outputs and generated media under |
| `AgentPolicies/<profile>/results/<benchmark>/`; the reporting implementation belongs to |
| `benchkit/`. Benchmark documentation must not accumulate model-run diaries. |
|
|
| ## Integration acceptance |
|
|
| An adapter contribution needs a pinned upstream evaluator, reproducible |
| environment/asset instructions, the native protocol, a selected episode plan, |
| and dependency-light checks for filtering, action semantics, counters, scoring |
| delegation and cleanup. Registration and runtime source/package allowlists must |
| include the new extension without recursively capturing assets or results. |
|
|
| Validate from a separate, stable source snapshot. CPU fixtures and a successful |
| package import do not prove native parity. Any authorized native validation is |
| a separately recorded run through the same interface, with failures retained. |
| See the repository [workflow](../../docs/evaluation.md) for current entrypoints |
| and the individual benchmark's protocol for native readiness. |
|
|
