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| from openenv.core.env_client import EnvClient | |
| from openenv.core.client_types import StepResult | |
| from models import ActionModel, ObservationModel, StateModel | |
| class DataDojoEnv(EnvClient[ActionModel, ObservationModel, StateModel]): | |
| def _step_payload(self, action: ActionModel)->dict: | |
| return action.model_dump(exclude_none=True) | |
| def _parse_result(self, payload: dict) -> StepResult: | |
| obs_data = payload.get("observation", {}) | |
| return StepResult( | |
| observation=ObservationModel( | |
| done=obs_data.get("done", False), | |
| reward=obs_data.get("reward", 0.0), | |
| metadata=obs_data.get("metadata", {}), | |
| data_schema=obs_data.get("data_schema", {}), | |
| NaNs=obs_data.get("NaNs", {}), | |
| sample=obs_data.get("sample", []), | |
| info=obs_data.get("info", ""), | |
| EDA=obs_data.get("EDA", None) | |
| ), | |
| reward=payload.get("reward", 0.0), | |
| done=payload.get("done", False), | |
| ) | |
| def _parse_state(self, payload: dict) -> StateModel: | |
| return StateModel( | |
| episode_id=payload.get("episode_id"), | |
| step_count=payload.get("step_count"), | |
| difficulty=payload.get("difficulty"), | |
| max_steps=payload.get("max_steps"), | |
| ) |