Add UI for model

app.py

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+import gradio as gr
+import pandas as pd
+import joblib
+
+# load full pipeline
+model = joblib.load("model.joblib")
+
+def predict_excel(file):
+    # Read uploaded Excel file
+    df = pd.read_excel(file.name)
+
+    # Check if required columns exist
+    required_cols = [
+        "CustomerID", "Tenure", "PreferredLoginDevice", "CityTier",
+        "WarehouseToHome", "PreferredPaymentMode", "Gender", "HourSpendOnApp",
+        "NumberOfDeviceRegistered", "PreferredOrderCat", "SatisfactionScore",
+        "MaritalStatus", "NumberOfAddress", "Complain",
+        "OrderAmountHikeFromlastYear", "CouponUsed", "OrderCount",
+        "DaySinceLastOrder", "CashbackAmount"
+    ]
+
+    missing = [c for c in required_cols if c not in df.columns]
+    if missing:
+        return f"❌ Missing columns in Excel: {missing}"
+
+    # Predict
+    preds = model.predict(df[required_cols])
+
+    # Add prediction column
+    df["Prediction"] = preds
+
+    # Save to new Excel file
+    out_path = "predicted_output.xlsx"
+    df.to_excel(out_path, index=False)
+
+    return out_path  # Gradio will let user download it
+
+# Gradio UI
+demo = gr.Interface(
+    fn=predict_excel,
+    inputs=gr.File(label="Upload Excel File (.xlsx)"),
+    outputs=gr.File(label="Download Updated Excel With Predictions"),
+    title="Excel-Based Customer Churn Predictor",
+    description="Upload an Excel file to receive a new Excel file with model predictions added."
+)
+
+demo.launch()

model.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1793d656c56c9a40407d5dcdcc5bc5b286eed5ff5ed212e14d0e0736ed5b85a7
+size 507659

requirements.txt

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+gradio
+pandas
+numpy
+scikit-learn
+joblib
+openpyxl