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cc6e5ac | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | from typing import Dict
from openenv.core import EnvClient
from openenv.core.client_types import StepResult
from openenv.core.env_server.types import State
try:
from .models import TICEAction, TICEObservation
except (ImportError, ModuleNotFoundError):
from models import TICEAction, TICEObservation
class TICEEnv(EnvClient[TICEAction, TICEObservation, State]):
def _step_payload(self, action: TICEAction) -> Dict:
return action.model_dump(exclude_none=True)
def _parse_result(self, payload: Dict) -> StepResult[TICEObservation]:
obs_data = payload.get("observation", {})
observation = TICEObservation(
tumor_trend=obs_data.get("tumor_trend", "stable"),
detection_signal=obs_data.get("detection_signal", 0.0),
t_cell_effectiveness=obs_data.get("t_cell_effectiveness", "low"),
resource_level=obs_data.get("resource_level", "moderate"),
b_cell_fatigue=obs_data.get("b_cell_fatigue", 0.0),
t_cell_fatigue=obs_data.get("t_cell_fatigue", 0.0),
recent_outcome=obs_data.get("recent_outcome", "no_effect"),
timestep=obs_data.get("timestep", 0),
episode_phase=obs_data.get("episode_phase", "early"),
archetype=obs_data.get("archetype", ""),
difficulty=obs_data.get("difficulty", ""),
feedback=obs_data.get("feedback", ""),
done=payload.get("done", obs_data.get("done", False)),
reward=payload.get("reward", obs_data.get("reward", 0.0)),
metadata=obs_data.get("metadata", {}),
)
return StepResult(
observation=observation,
reward=payload.get("reward"),
done=payload.get("done", False),
)
def _parse_state(self, payload: Dict) -> State:
return State(
episode_id=payload.get("episode_id"),
step_count=payload.get("step_count", 0),
)
TiceEnv = TICEEnv
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