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app.py

@@ -52,11 +52,15 @@ def predict_sales():
     # Make prediction (get log_price)
     predicted_log_price = model.predict(input_data)[0]
 
+    # Clip log price to avoid overflow
+    safe_log_price = np.clip(predicted_log_price, a_min=None, a_max=700)
+
     # Calculate actual price
-    predicted_price = np.exp(predicted_log_price)
+    predicted_price = np.exp(safe_log_price)
 
     # Convert predicted_price to Python float
     predicted_price = round(float(predicted_price), 2)
+
     # The conversion above is needed as we convert the model prediction (log price) to actual price using np.exp, which returns predictions as NumPy float32 values.
     # When we send this value directly within a JSON response, Flask's jsonify function encounters a datatype error