Delete app.py

app.py

@@ -1,51 +0,0 @@
-import requests
-import streamlit as st
-import pandas as pd
-
-st.title("Customer Churn Prediction")
-
-# Input fields for customer data
-CustomerID = st.number_input("Customer ID", min_value=10000000, max_value=99999999)
-CreditScore = st.number_input("Credit Score (customer's credit score)", min_value=300, max_value=900, value=650)
-Geography = st.selectbox("Geography (country where the customer resides)", ["France", "Germany", "Spain"])
-Age = st.number_input("Age (customer's age in years)", min_value=18, max_value=100, value=30)
-Tenure = st.number_input("Tenure (number of years the customer has been with the bank)", value=12)
-Balance = st.number_input("Account Balance (customer’s account balance)", min_value=0.0, value=10000.0)
-NumOfProducts = st.number_input("Number of Products (number of products the customer has with the bank)", min_value=1, value=1)
-HasCrCard = st.selectbox("Has Credit Card?", ["Yes", "No"])
-IsActiveMember = st.selectbox("Is Active Member?", ["Yes", "No"])
-EstimatedSalary = st.number_input("Estimated Salary (customer’s estimated salary)", min_value=0.0, value=50000.0)
-
-customer_data = {
-    'CreditScore': CreditScore,
-    'Geography': Geography,
-    'Age': Age,
-    'Tenure': Tenure,
-    'Balance': Balance,
-    'NumOfProducts': NumOfProducts,
-    'HasCrCard': 1 if HasCrCard == "Yes" else 0,
-    'IsActiveMember': 1 if IsActiveMember == "Yes" else 0,
-    'EstimatedSalary': EstimatedSalary
-}
-
-if st.button("Predict", type='primary'):
-    response = requests.post("https://praneeth232-demo-cont.hf.space/v1/customer", json=customer_data)
-    if response.status_code == 200:
-        result = response.json()
-        churn_prediction = result["Churn expected?"]  # Extract only the value
-        st.write(f"Based on the information provided, the customer with ID {CustomerID} is likely to {churn_prediction}.")
-    else:
-        st.error("Error in API request")
-
-# Batch Prediction
-st.subheader("Batch Prediction")
-file = st.file_uploader("Upload CSV file", type=["csv"])
-if file is not None:
-    if st.button("Predict for Batch", type='primary'):
-        response = requests.post("https://praneeth232-demo-cont.hf.space/v1/customerbatch", files={"file": file})
-        if response.status_code == 200:
-            result = response.json()
-            st.header("Batch Prediction Results")
-            st.write(result)
-        else:
-            st.error("Error in API request")