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models.py

@@ -16,7 +16,6 @@ from pydantic import BaseModel, Field
 from typing import Any, Dict, List, Optional
 
 
-
 from openenv.core.env_server.types import Action, Observation, State
 
 

rewards.py

@@ -17,7 +17,9 @@ class RewardProvider(Protocol):
     def reset(self) -> None:
         """Clear any internal state before a new episode."""
 
-    def compute(self, *, action: TextArenaAction, observation: TextArenaObservation) -> Dict[str, float]:
+    def compute(
+        self, *, action: TextArenaAction, observation: TextArenaObservation
+    ) -> Dict[str, float]:
         """Return a mapping of reward names to float values for the step."""
 
 
@@ -92,12 +94,16 @@ class _WordleRewardProvider:
     def reset(self) -> None:
         self._guess_history.clear()
 
-    def compute(self, *, action: TextArenaAction, observation: TextArenaObservation) -> Dict[str, float]:
+    def compute(
+        self, *, action: TextArenaAction, observation: TextArenaObservation
+    ) -> Dict[str, float]:
         guess = extract_guess(action.message)
         feedback = extract_wordle_feedback(observation)
 
         normalized_guess = guess if guess and guess != "[dunno]" else ""
-        previous_occurrences = self._guess_history.get(normalized_guess, 0) if normalized_guess else 0
+        previous_occurrences = (
+            self._guess_history.get(normalized_guess, 0) if normalized_guess else 0
+        )
 
         green_score = 0.0
         yellow_score = 0.0

server/environment.py

@@ -38,6 +38,17 @@ except ImportError:
 
 _TEXTARENA_MODULE: Any | None = None
 _TEXTARENA_IMPORT_ERROR: Exception | None = None
+_NLTK_DOWNLOADED: bool = False
+
+
+def _ensure_nltk_data() -> None:
+    """Download NLTK data once per process."""
+    global _NLTK_DOWNLOADED
+    if _NLTK_DOWNLOADED:
+        return
+    nltk.download("words", quiet=True)
+    nltk.download("averaged_perceptron_tagger_eng", quiet=True)
+    _NLTK_DOWNLOADED = True
 
 
 def _import_textarena() -> Any:
@@ -85,8 +96,7 @@ class TextArenaEnvironment(Environment):
         ta = _import_textarena()
 
         if download_nltk:
-            nltk.download("words", quiet=True)
-            nltk.download("averaged_perceptron_tagger_eng", quiet=True)
+            _ensure_nltk_data()
 
         self.env_id = env_id
         self.num_players = num_players