drugenv-trainer / client.py
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initial: drugenv trainer control panel
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"""Drug Target Validation Environment Client.
Provides the ``DrugTargetEnv`` class that communicates with the
environment server over WebSocket / HTTP using the OpenEnv protocol.
"""
from typing import Dict
from openenv.core.client_types import StepResult
from openenv.core.env_server.types import State
from openenv.core import EnvClient
try: # pragma: no cover - package import path
from .models import DrugTargetAction, ValidationObservation
except ImportError: # pragma: no cover - direct module import path
from models import DrugTargetAction, ValidationObservation
class DrugTargetEnv(
EnvClient[DrugTargetAction, ValidationObservation, State]
):
"""Client for the Drug Target Validation Environment.
Example:
>>> with DrugTargetEnv(base_url="http://localhost:8000") as env:
... result = env.reset()
... print(result.observation.target_gene)
... result = env.step(DrugTargetAction(
... action_type="query_expression",
... parameters={"database": "GTEx"},
... reasoning="baseline expression survey",
... ))
... print(result.observation.latest_output.summary)
"""
def _step_payload(self, action: DrugTargetAction) -> Dict:
return action.model_dump()
def _parse_result(
self, payload: Dict
) -> StepResult[ValidationObservation]:
obs_data = payload.get("observation", {})
observation = ValidationObservation(**obs_data)
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),
)