fixed buld obs

server/env.py

@@ -218,29 +218,22 @@ class EcoLLMInferenceRoutingEnvironment(Environment[RLAction, RLObservation, RLS
         )
 
     def _build_observation(self, reward: RLReward, done: bool) -> RLObservation:
-    query = self.current_task.queries[-1] if done else self.current_query
-    
-    # compute normalized score only at episode end
-    final_score = 0.0
-    if done:
-        max_possible = float(len(self.current_task.queries))
-        final_score = min(self._state.total_score / max_possible, 1.0) if max_possible > 0 else 0.0
-    
-    return RLObservation(
-        query=query.text,
-        cache_contents=self.cache_contents,
-        carbon_intensity=self.current_carbon_intensity,
-        done=done,
-        reward=reward.total_reward,
-        reward_details=reward,
-        kb_available=query.kb_available,
-        score=reward.score if done else 0.0,   # ← ADD THIS
-        metadata={
-            "task_id": self.current_task.task_id,
-            "difficulty": self.current_task.difficulty,
-            "state": self._state.public_payload(),
-        },
-    )
+        query = self.current_task.queries[-1] if done else self.current_query
+        return RLObservation(
+            query=query.text,
+            cache_contents=self.cache_contents,
+            carbon_intensity=self.current_carbon_intensity,
+            done=done,
+            reward=reward.total_reward,
+            reward_details=reward,
+            kb_available=query.kb_available,
+            score=reward.score if done else 0.0,
+            metadata={
+                "task_id": self.current_task.task_id,
+                "difficulty": self.current_task.difficulty,
+                "state": self._state.public_payload(),
+            },
+        )
 
     def _empty_reward(self, trace: list[str]) -> RLReward:
         return RLReward(