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app.py

@@ -1,18 +1,20 @@
+
 import streamlit as st
 import requests
 
-st.title("Product Sales Prediction")
+st.title("SuperKart Sales Predictor")
 
+# Input fields for product and store data
 Product_Weight = st.number_input("Product Weight", min_value=0.0, value=12.66)
 Product_Sugar_Content = st.selectbox("Product Sugar Content", ["Low Sugar", "Regular", "No Sugar"])
-Product_Allocated_Area = st.number_input("Product Allocated Area", min_value=0.0, value=0.0)
-Product_MRP = st.number_input("Product MRP", min_value=0.0, value=0.0)
-Store_Size = st.number_input("Store Size", min_value=0.0, value=0.0)
-Store_Location_City_Type = st.selectbox("Store Location City Type", ["Type 1", "Type 2", "Type 3"])
-Store_Type = st.selectbox("Store Type", ["Type A", "Type B", "Type C"])
-Product_Id_char = st.text_input("Product Id char", "")
-Store_Age_Years = st.number_input("Store Age Years", min_value=0.0, value=0.0)
-Product_Type_Category = st.selectbox("Product Type Category", ["Category A", "Category B", "Category C"])
+Product_Allocated_Area = st.number_input("Product Allocated Area (sq.ft)", min_value=0.0)
+Product_MRP = st.number_input("Product MRP (₹)", min_value=0.0)
+Store_Size = st.selectbox("Store Size", ["Small", "Medium", "High"])
+Store_Location_City_Type = st.selectbox("Store Location City Type", ["Tier 1", "Tier 2", "Tier 3"])
+Store_Type = st.selectbox("Store Type", ["Supermarket", "Grocery", "Convenience", "Department"])
+Product_Id_char = st.text_input("Product ID Character")
+Store_Age_Years = st.number_input("Store Age (Years)", min_value=0)
+Product_Type_Category = st.selectbox("Product Type Category", ["Food", "Non-Consumable", "Drinks"])
 
 product_data = {
     "Product_Weight": Product_Weight,
@@ -27,14 +29,14 @@ product_data = {
     "Product_Type_Category": Product_Type_Category
 }
 
-if st.button("Predict", type="primary"):
+if st.button("Predict", type='primary'):
     response = requests.post(
-        "https://MichaelNieto-superkart-backend.hf.space/v1/predict",
+        "https://MichaelNieto-superkart_backend.hf.space/v1/predict",
         json=product_data
     )
     if response.status_code == 200:
         result = response.json()
         predicted_sales = result["Sales"]
-        st.write(f"Predicted Product Sales Total: {predicted_sales:.2f}")
+        st.write(f"Predicted Product Store Sales Total: ₹{predicted_sales:.2f}")
     else:
         st.error("Error in API request")

requirements.txt

@@ -1,2 +1,2 @@
-streamlit==1.32.2
 requests==2.32.3
+streamlit==1.43.2