Update main.py

main.py

@@ -25,37 +25,36 @@ def home():
 # @app.route("/predict", methods=["POST"])
 @app.route("/predict")
 def predict():
-    return "predicted brooo"
-    # try:
-    #     # Debugging: print input code to check if the request is received correctly
-    #     print("Received code:", request.get_json()["code"])
+    try:
+        # Debugging: print input code to check if the request is received correctly
+        print("Received code:", request.get_json()["code"])
 
-    #     data = request.get_json()
-    #     if "code" not in data:
-    #         return jsonify({"error": "Missing 'code' parameter"}), 400
+        data = request.get_json()
+        if "code" not in data:
+            return jsonify({"error": "Missing 'code' parameter"}), 400
 
-    #     code_input = data["code"]
+        code_input = data["code"]
 
-    #     # Tokenize the input code using the CodeBERT tokenizer
-    #     inputs = tokenizer(
-    #         code_input,
-    #         return_tensors='pt',
-    #         truncation=True,
-    #         padding='max_length',
-    #         max_length=512
-    #     )
+        # Tokenize the input code using the CodeBERT tokenizer
+        inputs = tokenizer(
+            code_input,
+            return_tensors='pt',
+            truncation=True,
+            padding='max_length',
+            max_length=512
+        )
 
-    #     # Make prediction using the model
-    #     with torch.no_grad():
-    #         outputs = model(**inputs)
-    #         prediction = outputs.logits.squeeze().item()  # Extract the predicted score (single float)
+        # Make prediction using the model
+        with torch.no_grad():
+            outputs = model(**inputs)
+            prediction = outputs.logits.squeeze().item()  # Extract the predicted score (single float)
 
-    #     print(f"Predicted score: {prediction}")  # Debugging: Print prediction
+        print(f"Predicted score: {prediction}")  # Debugging: Print prediction
 
-    #     return jsonify({"predicted_score": prediction})
+        return jsonify({"predicted_score": prediction})
 
-    # except Exception as e:
-    #     return jsonify({"error": str(e)}), 500
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
 
 
 # Run the Flask app