Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| import requests | |
| st.title("SuperKart Sales Prediction App") #Complete the code to define the title of the app. | |
| # 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=10.0) #Complete the code to define the UI element for Product_Allocated_Area | |
| Product_MRP = st.number_input("Product MRP", min_value=0.0, value=10.0) #Complete the code to define the UI element for Product_MRP | |
| Store_Size = st.selectbox("Store Size", ["Small", "Medium", "High"]) #Complete the code to define the UI element for Store_Size | |
| Store_Location_City_Type = st.selectbox("Store Location City Type", ["Tier 1", "Tier 2", "Tier 3"]) #Complete the code to define the UI element for Store_Location_City_Type | |
| Store_Type = st.selectbox("Store Type", ["Departmental Store", "Food Mart", "Supermarket Type1", "Supermarket Type2"]) #Complete the code to define the UI element for Store_Type | |
| Product_Id_char = st.selectbox("Product Id char", ["FD", "NC", "DR"]) #Complete the code to define the UI element for Product_Id_char | |
| Store_Age_Years = st.number_input("Store Age Years", min_value=1, max_value=100,value=5) #Complete the code to define the UI element for Store_Age_Years | |
| Product_Type_Category = st.selectbox("Product Type Category", ["Low Sugar", "Regular", "No Sugar"]) #Complete the code to define the UI element for Product_Type_Category | |
| product_data = { | |
| "Product_Weight": Product_Weight, | |
| "Product_Sugar_Content": str(Product_Sugar_Content), | |
| "Product_Allocated_Area": Product_Allocated_Area, | |
| "Product_MRP": Product_MRP, | |
| "Store_Size": str(Store_Size), | |
| "Store_Location_City_Type": str(Store_Location_City_Type), | |
| "Store_Type": str(Store_Type), | |
| "Product_Id_char": str(Product_Id_char), | |
| "Store_Age_Years": Store_Age_Years, | |
| "Product_Type_Category": str(Product_Type_Category) | |
| } | |
| #if st.button("Predict", type='primary'): | |
| # response = requests.post("https://jamolo12-SuperKart.hf.space/v1/predict", json=product_data) # Complete the code to enter user name and space name to correctly define the endpoint | |
| # if response.status_code == 200: | |
| # result = response.json() | |
| # predicted_sales = result["Sales"] | |
| # st.write(f"Predicted Product Store Sales Total: ₹{predicted_sales:.2f}") | |
| # else: | |
| # st.error("Error in API request") | |
| if st.button("Predict", type='primary'): | |
| try: | |
| response = requests.post("https://jamolo12-SuperKart.hf.space/v1/predict", json=product_data) | |
| if response.status_code == 200: | |
| result = response.json() | |
| predicted_sales = result["Sales"] | |
| st.write(f"Predicted Product Store Sales Total: ₹{predicted_sales:.2f}") | |
| else: | |
| # Display a more detailed error message from the API | |
| st.error(f"Error in API request: Status Code {response.status_code}") | |
| try: | |
| # Try to show the JSON error response from the API | |
| error_details = response.json() | |
| st.error(f"Details: {error_details}") | |
| except ValueError: | |
| # If the error response is not in JSON format, show the raw text | |
| st.error(f"Details: {response.text}") | |
| except requests.exceptions.RequestException as e: | |
| # Handle network-level errors like connection issues | |
| st.error(f"A connection error occurred: {e}") | |