Upload app.py

app.py

@@ -41,8 +41,6 @@ logger = logging.getLogger(__name__)
 label_mapping = {0: "✅ Correct", 1: "🤔 Conceptually Flawed", 2: "🔢 Computationally Flawed"}
 
 
-
-
 # ===================================================================
 # 1. DEFINE CUSTOM CLASSIFIER (Required for Phi-4)
 # ===================================================================
@@ -165,7 +163,7 @@ classifier_tokenizer = None
 
 def load_model():
     """Load your trained model here"""
-    global gemma_model, gemma_tokenizer, classifier_model, classifier_tokenizer, DEVICE
+    global gemma_model, gemma_tokenizer, classifier_model, classifier_tokenizer
     
     try:
         device = DEVICE
@@ -238,6 +236,8 @@ def run_conceptual_check(question: str, solution: str, model, tokenizer) -> dict
     """
     STAGE 1: Runs the Phi-4 classifier with memory optimizations.
     """
+    device = DEVICE
+    
     input_text = f"{CLASSIFIER_SYSTEM_PROMPT}\n\n### Problem:\n{question}\n\n### Answer:\n{solution}"
     inputs = tokenizer(
         input_text,
@@ -267,6 +267,8 @@ def run_computational_check(solution: str, model, tokenizer, batch_size: int = 3
     STAGE 2: Splits a solution into lines and performs a batched computational check.
     (Corrected to handle PEMDAS/parentheses)
     """
+    device = DEVICE
+    
     lines = [line.strip() for line in solution.strip().split('\n') if line.strip() and "FINAL ANSWER:" not in line.upper()]
     if not lines:
         return {"error": False}
@@ -424,7 +426,7 @@ with gr.Blocks(title="Math Solution Classifier", theme=gr.themes.Soft()) as app:
     classify_btn.click(
         fn=classify_solution,
         inputs=[question_input, solution_input],
-        outputs=[classification_output, confidence_output, explanation_output]
+        outputs=[classification_output, explanation_output]
     )
 
 if __name__ == "__main__":