Spaces:
Sleeping
Sleeping
File size: 3,595 Bytes
6fe6a92 701565d 560d456 6fe6a92 701565d 6fe6a92 449a524 6fe6a92 560d456 449a524 6fe6a92 449a524 6fe6a92 45b3c20 6fe6a92 45b3c20 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
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}")
|