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graders.py

@@ -0,0 +1,57 @@
+"""Root-level grader entry points for OpenEnv judge.
+
+Each function receives the episode trajectory and returns a float in [0.0, 1.0].
+These are referenced in openenv.yaml and must be importable from the repo root.
+"""
+
+from __future__ import annotations
+
+from typing import Any, Dict, List
+
+from server.graders import SchedulingGrader
+from server.scheduling_env_environment import SchedulingEnvironment
+
+_grader = SchedulingGrader()
+_env = SchedulingEnvironment()
+
+
+def _grade_task(task_id: str, trajectory: Any = None) -> float:
+    """Run a task with the environment's own state and grade it.
+
+    If a trajectory dict is provided with 'final_state' and 'final_observation',
+    those are used directly. Otherwise the grader returns 0.0.
+    """
+    if trajectory is not None:
+        final_state = trajectory.get("final_state")
+        final_obs = trajectory.get("final_observation")
+        if final_state and final_obs:
+            return _grader.grade_episode(final_state, final_obs)
+
+    # Fallback: use the environment's current state
+    state = _env.state
+    if state.completed:
+        from models import SchedulingObservation
+
+        obs = SchedulingObservation(
+            success=True,
+            done=True,
+            reward=state.final_reward,
+        )
+        return _grader.grade_episode(state, obs)
+
+    return 0.0
+
+
+def task1_easy_grader(trajectory: Any = None) -> float:
+    """Grader for task1_easy: 2 attendees, free slot exists. Expected: 0.8-1.0."""
+    return _grade_task("task1_easy", trajectory)
+
+
+def task2_medium_grader(trajectory: Any = None) -> float:
+    """Grader for task2_medium: 4 attendees, requires rescheduling. Expected: 0.5-0.8."""
+    return _grade_task("task2_medium", trajectory)
+
+
+def task3_hard_grader(trajectory: Any = None) -> float:
+    """Grader for task3_hard: 6 attendees, cascading conflicts. Expected: 0.2-0.6."""
+    return _grade_task("task3_hard", trajectory)

openenv.yaml

@@ -5,3 +5,13 @@ runtime: fastapi
 app: server.app:app
 port: 8000
 description: "Intelligent Meeting Scheduling - Learn optimal scheduling through multi-stakeholder preference optimization"
+tasks:
+  - id: task1_easy
+    difficulty: easy
+    grader: graders.task1_easy_grader
+  - id: task2_medium
+    difficulty: medium
+    grader: graders.task2_medium_grader
+  - id: task3_hard
+    difficulty: hard
+    grader: graders.task3_hard_grader