| # SimplerEnv |
|
|
| This integration follows the [RoboDojo-derived service conventions](../SERVICE_CONVENTIONS.md). |
| Its native delta actions, sensor tracks and final-step scoring remain SimplerEnv-specific. |
|
|
| This benchmark can run as an independent SIM service via [server.py](server.py). |
| Start from [server.example.json](server.example.json), adjust deployment paths/GPU |
| before launch, and follow the [shared server workflow](../SERVER_PROTOCOL.md). |
| The server owns native reset/control/scoring; the evaluator uses the client, and |
| the model receives only permitted observations. Native service-mode validation is separate from adapter availability. |
|
|
| Evaluate a policy through `SimplerEnvBenchmarkAdapter`: the model receives only |
| declared observations and returns action chunks; the adapter owns the simulator, |
| controller and native scoring. No model training is required. |
|
|
| - [Evaluation protocol](EVALUATION_PROTOCOL.md): fast/full scope, budgets and scoring. |
| - [Tasks and variants](bench_server/protocol/TASKS.md): 25 aliases, 15 canonical subtasks and native VM/VA matrices. |
| - [Policy interface](bench_server/protocol/INTERFACE.md): observations, actions, transport and isolation. |
| - [Rendering checks](environment/RENDERING.md): preflight and graphics-driver troubleshooting. |
|
|
| The prepackaged fast track is executable. Native full VM/VA evaluation is |
| documented but is not yet implemented by the unified adapter; fast results must |
| not be presented as full reference scores. |
|
|
| ## Directory responsibilities |
|
|
| ```text |
| SimplerEnv/ |
| ├── server.py # stable public launch entrypoint |
| ├── server.example.json # example deployment and selected-track settings |
| ├── bench_server/ |
| │ ├── adapter.py # native bridge, observation allowlist and scoring |
| │ └── protocol/ # task catalog, selection plan and interface reference |
| ├── environment/ # upstream pins, installation and rendering checks |
| └── checks/ # dependency-light integration/boundary checks |
| ``` |
|
|
| `bench_server/protocol/` is benchmark definition data, not simulator assets or |
| server credentials. The catalog's bytes and task order are unchanged by this |
| layout migration. [plan.py](bench_server/protocol/plan.py) owns task selection. |
| The canonical adapter lives in `bench_server/adapter.py` and lazily |
| imports the native simulator on reset, solely inside the service process. |
| Model prompts, action selection and results stay under `AgentPolicies/<profile>/`; |
| `benchkit/` supplies shared records, source capture and reports. |
|
|
| ## Launch the benchmark service |
|
|
| After verifying the native environment, copy `server.example.json` to your own |
| configuration and select its task, device, observation track and budgets before |
| launch. The example selects the horizontal-can task's native 80-control horizon, |
| `interaction_mode: "agent_method"` and explicit action-rejection feedback. A |
| method's decision-call cap and action prefix are configured on its driver; they |
| do not extend the native horizon. The separately labeled decision-budget track |
| remains available when explicitly selected. Use a fresh output directory: |
|
|
| On multi-GPU hosts, first run the [renderer-only device preflight](environment/RENDERING.md#first-verify-the-actual-gpu-without-starting-a-task). |
| Keep its exact `device` selector and add `"expected_gpu_uuid": "GPU-..."` |
| (the complete verified UUID) to the server parameters. This optional deployment |
| assertion rejects an unexpected physical device before any public observation; |
| it never silently selects a replacement GPU. CUDA ordinal visibility is not |
| proof of Vulkan device selection. |
|
|
| ```bash |
| # Activate the native SimplerEnv environment first; set this secret privately. |
| export RSI_SIM_SERVER_TOKEN='<32-or-more-character-random-URL-safe-secret>' |
| python -B -m benchmarks.simBenchmarks.SimplerEnv.server \ |
| --parameters /absolute/path/to/simpler-server.json \ |
| --seed 0 --episodes 1 --port 8765 \ |
| --output-dir /absolute/path/to/AgentPolicies/your_agent/results/simpler_env/raw/your-run/server |
| ``` |
|
|
| The listener binds loopback. Use the [shared transport](../SERVER_PROTOCOL.md) |
| for a trusted driver on another machine. Keep its bearer token and administrative |
| client out of the model actor's workspace. There is no background control tick |
| while the policy is thinking; lost action acknowledgments are not replayed. |
| Each predeclared episode is claimed once, including failures. |
|
|
| The service preserves this benchmark's seven-value delta-action interface; |
| it does **not** expose RoboDojo's absolute dual-arm EEF16 action or robot-feedback |
| extension. Choose a compatible agent method, not an action-vector conversion |
| guessed by a server. Explicitly select `interaction_mode: "agent_method"` for |
| methods that use internal inference or local tools over permitted public data, |
| including the current Codex CLI method. This adds `/agent-method` before `/v1` |
| in the selected protocol identity. Omission or `"single_response"` preserves |
| the historical one-provider-request-per-call track and its existing ID. Neither |
| the service nor the CLI wrapper verifies hidden provider request counts. The |
| new mode grants no extra observations, native access, resets or control budget; |
| see [interaction modes](EVALUATION_PROTOCOL.md#interaction-modes). |
|
|
| The example explicitly selects `"action_rejection_feedback": true`, as required |
| by the current Codex native-vector driver's default feedback behavior. |
| This adds `/action-feedback` before the optional `/agent-method` and final `/v1` |
| suffixes: a rejected action does |
| not execute, and its bounded validation issue reaches the next counted call |
| with the last acknowledged observation. The omitted/default `false` setting |
| preserves historical fail-fast semantics. The selected flag is captured in the |
| service parameters; see [the protocol](EVALUATION_PROTOCOL.md#optional-rejected-action-feedback). |
|
|
| ## Install the evaluation environment |
|
|
| Use a Linux NVIDIA node with a separate Python 3.10 environment. From the |
| repository root: |
|
|
| ```bash |
| conda env create -f benchmarks/simBenchmarks/SimplerEnv/environment/environment.yml |
| conda activate starvla-rsi-simpler |
| |
| export SIMPLERENV_ROOT=/absolute/path/to/benchmarks/SimplerEnv |
| git clone --recurse-submodules https://github.com/allenai/SimplerEnv.git "$SIMPLERENV_ROOT" |
| git -C "$SIMPLERENV_ROOT" checkout c701ea271b16b80616d6fed9713c4a50a0adea3b |
| git -C "$SIMPLERENV_ROOT" submodule update --init --recursive |
| |
| python -m pip install \ |
| -c benchmarks/simBenchmarks/SimplerEnv/environment/constraints.txt \ |
| -e "$SIMPLERENV_ROOT/ManiSkill2_real2sim" -e "$SIMPLERENV_ROOT" -e . |
| ``` |
|
|
| The submodule pin is `ef7a4d4fdf4b69f2c2154db5b15b9ac8dfe10682`. |
| The adapter checks upstream revisions and tracked modifications before reset. |
| Use the assets shipped with the pinned recursive checkout. Model checkpoints, |
| training data and a StarVLA model server are not required. |
|
|
| The constraints avoid incompatible NumPy/OpenCV combinations and select an |
| available Ruckig wheel. If your deployment requires a network proxy, use its |
| existing configuration; do not put credentials into protocols or model files. |
|
|
| ## Validate graphics before evaluating a model |
|
|
| CUDA visibility alone is insufficient: the native renderer also needs graphics |
| libraries and a working NVIDIA Vulkan ICD. Prefer your system's NVIDIA ICD. If |
| the graphics library is already installed but the container lacks its ICD |
| registration, this process-local example uses the provided descriptor: |
|
|
| ```bash |
| export VK_ICD_FILENAMES="$PWD/benchmarks/simBenchmarks/SimplerEnv/environment/nvidia_icd.json" |
| python benchmarks/simBenchmarks/SimplerEnv/environment/verify_environment.py |
| ``` |
|
|
| The verifier performs environment/reset/render and constant-action checks, not a |
| model evaluation. Use `--help` for task and diagnostic-step options. Check both |
| IBL and drawer-task RT rendering: a detailed photographic background can hide a |
| black robot or foreground. [RENDERING.md](environment/RENDERING.md) explains this distinction |
| and matching driver-data requirements. Simulator-free `catalog` or `list` |
| commands do not establish graphics readiness. |
|
|
| ## Connect an agent |
|
|
| After service readiness, launch a compatible model-owned driver. For the current |
| Codex native-vector method, follow [NATIVE_CONTROL.md](../../../AgentPolicies/gpt6_astra/docs/NATIVE_CONTROL.md). |
| Model configuration, prompts, memory and decision loops belong to that profile, |
| not this benchmark. The service exposes only its declared observation/action |
| contract, not a task-solving RPC or the simulator handle. |
|
|
| See [the evaluation workflow](../../../docs/evaluation.md) for source capture and |
| closed-record reporting. Protocol and call-accounting restrictions apply to each |
| selected method; a method name alone does not establish provider metering or native parity. |
|
|
| ## Results and offline review |
|
|
| Outputs belong under `AgentPolicies/<model-profile>/results/simpler_env/`: |
|
|
| - `raw/`: campaigns, manifests, event streams, responses, source snapshots and original media. |
| - `reports/` and `indices/`: task coverage, typed failures and hash-bound summaries. |
| - `media/`: presentation copies of closed videos, named with task IDs/descriptions. |
|
|
| Raw/media outputs are ignored by Git. Preserve original closed bytes and every |
| attempt, including failures. Do not expose closed artifacts to an active policy. |
|
|
| The primary score uses the final executed native step's success, not a video's |
| appearance, an actor's declaration or the best intermediate frame. Record |
| policy calls, executed action decisions, control steps and first-success timing |
| separately. First success is diagnostic, not a replacement score. |
|
|
| `harness_source/` binds shared and benchmark integration bytes; |
| `model_source/` separately binds declared policy/configuration/prompt bytes. |
| These are provenance records, not proof of OS isolation, loaded-memory identity, |
| native asset completeness or trusted provider accounting. |
|
|
| Use the shared [closed-record auditor](../../../benchkit/audits/closed_run.py), |
| [mailbox artifact auditor](../../../benchkit/audits/mailbox_artifacts.py) and |
| [progress reporter](../../../benchkit/reports/progress.py) on closed runs only. |
| Their `--help` commands describe supported inputs and limitations. A passed |
| record audit does not establish native baseline parity. Changing code or setup |
| requires a separately declared evaluation configuration, never rewritten results. |
|
|
| Use [the review checklist](../../../benchkit/audits/REVIEW_GUIDE.md) for independent |
| closed-run review. Shared video export is available as |
| `python -m benchkit.reports.export_videos --help`; it copies only closed evidence. |
| Historical anonymous results remain under |
| [the model result namespace](../../../AgentPolicies/anonymous_code_agent/results/simpler_env/README.md), |
| not in this benchmark's source directory. |
|
|
