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app.py

@@ -24,22 +24,22 @@ store_type = st.selectbox("Store Type ", ["Supermarket Type1", "Supermarket Type
 
 
 # Convert user input into a DataFrame
-input_data = pd.DataFrame([{
-    'Product_Weight': product_weight,
-    'Product_Sugar_Content': product_sugar_content,
-    'Product_Allocated_Area': product_allocated_area,
-    'Product_Type': product_type,
-    'Product_MRP': product_mrp,
-    'Store_Id': store_id,
-    'Store_Establishment_Year': store_establishment_year,
-    'Store_Size': store_size,
-    'Store_Location_City_Type': store_location_city_type,
-    'Store_Type': store_type
-}])
+input_data = {
+    'product_weight': product_weight,
+    'product_sugar_content': product_sugar_content,
+    'product_allocated_area': product_allocated_area,
+    'product_type': product_type,
+    'product_mrp': product_mrp,
+    'store_id': store_id,
+    'store_establishment_year': store_establishment_year,
+    'store_size': store_size,
+    'store_location_city_type': store_location_city_type,
+    'store_type': store_type
+}
 
 # Make prediction when the "Predict" button is clicked
 if st.button("Predict"):
-    response = requests.post("https://karora1804-StoreTotalSalesPredictionBackend.hf.space/v1/storeSales", json=input_data.to_dict(orient='records')[0])  # Send data to Flask API
+    response = requests.post("https://karora1804-StoreTotalSalesPredictionBackend.hf.space/v1/storeSales", json=input_data)  # Send data to Flask API
     if response.status_code == 200:
         prediction = response.json()['Predicted Total Sales:']
         st.success(f"Predicted Store Total Sales: {prediction}")