diff --git a/environments/text_reversal_environment.py b/environments/text_reversal_environment.py
index 903d5036..fbe2fd49 100644
--- a/environments/text_reversal_environment.py
+++ b/environments/text_reversal_environment.py
@@ -17,7 +17,6 @@ from atroposlib.envs.base import (
 )
 from atroposlib.utils.tokenize_for_trainer import tokenize_for_trainer
 
-
 # Thinking-enabled system prompt
 thinking_system_prompt = (
     "You are a deep thinking AI, you may use extremely long chains of thought to deeply consider the "
@@ -127,9 +126,9 @@ class TextReversalEnv(BaseEnv):
             wandb_metrics = {}
 
         try:
-            wandb_metrics["train/percent_correct"] = sum(self.percent_correct_buffer) / max(
-                1, len(self.percent_correct_buffer)
-            )
+            wandb_metrics["train/percent_correct"] = sum(
+                self.percent_correct_buffer
+            ) / max(1, len(self.percent_correct_buffer))
         except ZeroDivisionError:
             pass
 
@@ -151,7 +150,9 @@ class TextReversalEnv(BaseEnv):
           - user_content
           - expected_assistant
         """
-        dataset_name = getattr(self.config, "dataset_name", "PrimeIntellect/Reverse-Text-SFT")
+        dataset_name = getattr(
+            self.config, "dataset_name", "PrimeIntellect/Reverse-Text-SFT"
+        )
         eval_dataset_name = getattr(self.config, "eval_dataset_name", None)
         try:
             full_dataset = load_dataset(dataset_name, split="train")
@@ -229,7 +230,9 @@ class TextReversalEnv(BaseEnv):
 
         self.iter = 0
 
-    def _extract_fields(self, row: Dict) -> Tuple[Optional[str], Optional[str], Optional[str]]:
+    def _extract_fields(
+        self, row: Dict
+    ) -> Tuple[Optional[str], Optional[str], Optional[str]]:
         """Extract (system_text, user_text, expected_text) from a raw dataset row.
 
         Expected forms:
@@ -315,7 +318,9 @@ class TextReversalEnv(BaseEnv):
         completion = await self.server.completion(
             prompt=prompt,
             n=1,
-            max_tokens=getattr(self.config, "max_eval_token_length", self.config.max_token_length),
+            max_tokens=getattr(
+                self.config, "max_eval_token_length", self.config.max_token_length
+            ),
             temperature=0.2,
             split="eval",
         )
@@ -335,7 +340,9 @@ class TextReversalEnv(BaseEnv):
         percent_correct = sum(scores) / len(scores) if scores else 0.0
         self.eval_metrics.append(("eval/percent_correct", percent_correct))
 
-    async def collect_trajectories(self, item: Item) -> Tuple[Optional[ScoredDataGroup], List]:
+    async def collect_trajectories(
+        self, item: Item
+    ) -> Tuple[Optional[ScoredDataGroup], List]:
         # item: (prompt_messages_tuple, expected_text_string)
         prompt_messages_list = [dict(m) for m in item[0]]
 
@@ -346,7 +353,9 @@ class TextReversalEnv(BaseEnv):
         completions = await self.server.completion(
             prompt=prompt,
             n=self.config.group_size,
-            max_tokens=getattr(self.config, "max_train_token_length", self.config.max_token_length),
+            max_tokens=getattr(
+                self.config, "max_train_token_length", self.config.max_token_length
+            ),
             temperature=0.8,
         )
 
@@ -415,7 +424,9 @@ class TextReversalEnv(BaseEnv):
         item = self.train[self.iter % len(self.train)]
         self.iter += 1
 
-        messages = self._build_messages(item.get("system_content", ""), item.get("user_content", ""))
+        messages = self._build_messages(
+            item.get("system_content", ""), item.get("user_content", "")
+        )
 
         prompt_tuple = tuple(frozenset(m.items()) for m in messages)
         answer_text = item.get("expected_assistant", "")
@@ -433,7 +444,9 @@ class TextReversalEnv(BaseEnv):
         expected_text = item[1] if item else ""
         group_rows = []
         for i in range(min(num_keep, len(scored_data["tokens"]))):
-            decoded = self.tokenizer.decode(scored_data["tokens"][i], skip_special_tokens=False)
+            decoded = self.tokenizer.decode(
+                scored_data["tokens"][i], skip_special_tokens=False
+            )
             score_val = scored_data["scores"][i]
             group_rows.append((decoded, score_val, expected_text))
 
@@ -444,5 +457,3 @@ class TextReversalEnv(BaseEnv):
 
 if __name__ == "__main__":
     TextReversalEnv.cli()
-
-