diff --git a/evaluation_function/evaluation.py b/evaluation_function/evaluation.py
index f2d3cf1..f789f2b 100755
--- a/evaluation_function/evaluation.py
+++ b/evaluation_function/evaluation.py
@@ -5,53 +5,53 @@
 from .schemas.result import Result
 from .correction import analyze_fsa_correction
 
-def evaluation_function(
-    payload: Any
-) -> LFResult:
-  return LFResult(
-    is_correct=False,
-        feedback_items=[("error", f"{payload}")]
-    )
-
 # def evaluation_function(
-#     response: Any,
-#     answer: Any,
-#     params: Params,
+#     payload: Any
 # ) -> LFResult:
-#     """
-#     Evaluate a student's FSA response against the expected answer.
+#   return LFResult(
+#     is_correct=False,
+#         feedback_items=[("error", f"{payload}")]
+#     )
+
+def evaluation_function(
+    response: Any,
+    answer: Any,
+    params: Params,
+) -> LFResult:
+    """
+    Evaluate a student's FSA response against the expected answer.
     
-#     Args:
-#         response: Student's FSA (dict with states, alphabet, transitions, etc.), since frontend constriants, this is FSAFrontend
-#         answer: Expected FSA still, FSAFrontend for the same reason
-#         params: Extra parameters (e.g., require_minimal)
+    Args:
+        response: Student's FSA (dict with states, alphabet, transitions, etc.), since frontend constriants, this is FSAFrontend
+        answer: Expected FSA still, FSAFrontend for the same reason
+        params: Extra parameters (e.g., require_minimal)
     
-#     Returns:
-#         LFResult with is_correct and feedback
-#     """
-#     try:
-#         # Parse FSAs from input
-#         student_fsa_ = FSAFrontend.model_validate(response)
-#         expected_fsa_ = FSAFrontend.model_validate(answer)
+    Returns:
+        LFResult with is_correct and feedback
+    """
+    try:
+        # Parse FSAs from input
+        student_fsa_ = FSAFrontend.model_validate(response)
+        expected_fsa_ = FSAFrontend.model_validate(answer)
 
-#         student_fsa = student_fsa_.from_flattened()
-#         expected_fsa = expected_fsa_.from_flattened()
+        student_fsa = student_fsa_.from_flattened()
+        expected_fsa = expected_fsa_.from_flattened()
 
         
-#         # Get require_minimal from params if present
-#         require_minimal = params.get("require_minimal", False) if hasattr(params, "get") else False
+        # Get require_minimal from params if present
+        require_minimal = params.get("require_minimal", False) if hasattr(params, "get") else False
         
-#         # Run correction pipeline
-#         result: Result = analyze_fsa_correction(student_fsa, expected_fsa, require_minimal)
+        # Run correction pipeline
+        result: Result = analyze_fsa_correction(student_fsa, expected_fsa, require_minimal)
         
-#         # Convert to lf_toolkit Result
-#         return LFResult(
-#             is_correct=result.is_correct,
-#             feedback_items=[("feedback", result.feedback)]
-#         )
+        # Convert to lf_toolkit Result
+        return LFResult(
+            is_correct=result.is_correct,
+            feedback_items=[("feedback", result.feedback)]
+        )
         
-#     except Exception as e:
-#         return LFResult(
-#             is_correct=False,
-#             feedback_items=[("error", f"Invalid FSA format: {str(e)}, received: \n\nresponse: {response}\n\n answer: {answer}, \n\nparams: {params}")]
-#         )
+    except Exception as e:
+        return LFResult(
+            is_correct=False,
+            feedback_items=[("error", f"Invalid FSA format: {str(e)}, received: \n\nresponse: {response}\n\n answer: {answer}, \n\nparams: {params}")]
+        )