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9a3b69b 43f41de 9a3b69b eb1ebe6 43f41de eb1ebe6 9a3b69b | 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 52 53 54 55 56 57 58 59 60 61 62 63 | """Explainer Env Environment Client."""
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 ExplainerAction, ExplainerObservation
except ImportError: # pragma: no cover - supports direct test execution
from models import ExplainerAction, ExplainerObservation
class ExplainerEnv(
EnvClient[ExplainerAction, ExplainerObservation, State]
):
"""
Client for the Research → Interactive Explainer environment.
Example:
>>> with ExplainerEnv(base_url="http://localhost:8000").sync() as sc:
... result = sc.reset()
... # Explore phase
... result = sc.step(ExplainerAction(
... action_type="explore",
... tool="search_arxiv",
... query="attention mechanism transformers",
... intent="visual intuition and equations",
... ))
... # Generate phase
... result = sc.step(ExplainerAction(
... action_type="generate", format="marimo", code="import marimo..."
... ))
"""
def _step_payload(self, action: ExplainerAction) -> Dict:
return action.model_dump()
def _parse_result(self, payload: Dict) -> StepResult[ExplainerObservation]:
obs_data = payload.get("observation", {})
observation = ExplainerObservation(
**{
k: obs_data.get(k)
for k in ExplainerObservation.model_fields
if k in obs_data
},
done=payload.get("done", False),
reward=payload.get("reward", 0.0),
metadata=obs_data.get("metadata", {}),
)
return StepResult(
observation=observation,
reward=payload.get("reward", 0.0),
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),
)
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