app.py

import requests
import streamlit as st
import pandas as pd

st.title ("SuperKart Sales Forecast")

st.write ("Sales forecast for your product")


# Product Details
st.subheader ("Product Details")

prod_weight       = st.number_input ("Weight", min_value=0.0, max_value=200.0, value=10.0, step=0.1)
prod_alloc_area   = st.number_input ("Allocated Area (fraction 0-1)", min_value=0.0, max_value=1.0, value=0.1)
prod_mrp          = st.number_input ("MRP", min_value=0.0, max_value=1000.0, value=200.0, step=1.0)
prod_sug_content  = st.selectbox    ("Sugar Content", ['Low Sugar', 'Regular', 'No Sugar'])
prod_type         = st.selectbox    ("Product Type", [
    'Frozen Foods', 'Dairy', 'Canned', 'Baking Goods', 'Health and Hygiene',
    'Snack Foods', 'Meat', 'Household', 'Hard Drinks', 'Fruits and Vegetables',
    'Breads', 'Soft Drinks', 'Breakfast', 'Others', 'Starchy Foods', 'Seafood'
])

# Store Details
st.subheader ("Store Details")

# Dictionary mapping store IDs to establishment years
store_data = {
    'OUT001': 1987,
    'OUT002': 1998,
    'OUT003': 1999,
    'OUT004': 2009
}

# Store IDs and their corresponding establishment years
store_ids = ['OUT001', 'OUT002', 'OUT003', 'OUT004']
establishment_years = [1987, 1998, 1999, 2009]

# Create a mapping of store_id to year
store_map = dict(zip(store_ids, establishment_years))

# Dropdown for selecting Store ID
store_id = st.selectbox("Select Store ID", store_ids)

# Auto-select the corresponding establishment year (as single-option dropdown)
matched_year = store_map[store_id]
store_estb_year = st.selectbox("Establishment Year (auto-selected)", options=[matched_year], index=0, disabled=True)

store_size        = st.selectbox    ("Store Size", ['Small', 'Medium', 'High'])
store_city_type   = st.selectbox    ("Type of City", ['Tier 1', 'Tier 2', 'Tier 3'])
store_type        = st.selectbox    ("Store Type", ['Food Mart', 'Departmental Store', 'Supermarket Type1', 'Supermarket Type2'])


# Single sales forecast
if st.button("Forecast Sales for Single Product", type='primary'):

    # extract the data collected into a structure
    input_data = {
        'Product_Weight'            : prod_weight,
        'Product_Sugar_Content'     : prod_sug_content,
        'Product_Allocated_Area'    : prod_alloc_area,
        'Product_Type'              : prod_type,
        'Product_MRP'               : prod_mrp,
        'Store_Id'                  : store_id,
        'Store_Establishment_Year'  : store_estb_year,
        'Store_Size'                : store_size,
        'Store_Location_City_Type'  : store_city_type,
        'Store_Type'                : store_type
    }

    response = requests.post (
        "https://asvravi-SuperKartBE.hf.space/v1/SuperKartSales",
        json=input_data
        )
    if response.status_code == 200:
        result = response.json ()
        sales_forecast = result.get ("SalesForecast")  # Extract only the value
        st.success (f"The sales forecast for given input is {sales_forecast:.2f}.")
    else:
        st.error (f"Error in API request - {response.status_code}")

# ==============================
# Batch Prediction
# ==============================
st.subheader ("Batch Forecast of SuperKart Sales")

file = st.file_uploader ("Upload CSV file", type=["csv"])

if file is not None:

  if st.button("Forecast Sales for Batch", type='primary'):

      inputfile = {"file": (file.name, file.getvalue(), "text/csv")}
      response = requests.post(
          "https://asvravi-SuperKartBE.hf.space/v1/SuperKartBatchSales",
          files=inputfile
      )

      if response.status_code == 200:
          st.header("Batch Forecast Results")
          
          result = response.json ()

          # convert dict to dataframe for better display
          result_df = pd.DataFrame(list(result.items()), columns=["Product_Id", "Predicted_Sales"])
          result_df["Predicted_Sales"] = result_df["Predicted_Sales"].astype(float).round(2)
          st.dataframe (result_df)
          
          #st.write(result)
      else:
          st.error (f"Error in API request {response.status_code}")