Create app.py

app.py

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+import gradio as gr
+import pickle
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Load model
+with open("DecisionTreeClassifier.pkl", "rb") as file:
+    model = pickle.load(file)
+
+# Prediction function
+def predict_churn(age, gender, tenure, usage, support, delay,
+                  subscription, contract, spend, interaction):
+
+    # Convert categorical to numeric (must match training!)
+    gender_map = {"Male": 0, "Female": 1}
+    sub_map = {"Basic": 0, "Standard": 1, "Premium": 2}
+    contract_map = {"Monthly": 0, "Quarterly": 1, "Yearly": 2}
+
+    input_data = np.array([[ 
+        age,
+        gender_map[gender],
+        tenure,
+        usage,
+        support,
+        delay,
+        sub_map[subscription],
+        contract_map[contract],
+        spend,
+        interaction
+    ]])
+
+    # Prediction
+    pred = model.predict(input_data)[0]
+    prob = model.predict_proba(input_data)[0][1]
+
+    result = "Churn ⚠️" if pred == 1 else "No Churn 🙂"
+
+    # 📊 Graph: Probability Bar Chart
+    fig, ax = plt.subplots()
+    ax.bar(["No Churn", "Churn"], [1-prob, prob])
+    ax.set_title("Churn Probability")
+    ax.set_ylabel("Probability")
+
+    return result, f"{prob*100:.2f}%", fig
+
+
+# 🎨 Gradio UI
+interface = gr.Interface(
+    fn=predict_churn,
+    inputs=[
+        gr.Number(label="Age"),
+        gr.Dropdown(["Male", "Female"], label="Gender"),
+        gr.Number(label="Tenure"),
+        gr.Number(label="Usage Frequency"),
+        gr.Number(label="Support Calls"),
+        gr.Number(label="Payment Delay"),
+        gr.Dropdown(["Basic", "Standard", "Premium"], label="Subscription Type"),
+        gr.Dropdown(["Monthly", "Quarterly", "Yearly"], label="Contract Length"),
+        gr.Number(label="Total Spend"),
+        gr.Number(label="Last Interaction")
+    ],
+    outputs=[
+        gr.Text(label="Prediction"),
+        gr.Text(label="Churn Probability"),
+        gr.Plot(label="Graph")
+    ],
+    title="📊 Customer Churn Prediction System",
+    description="Enter customer details to predict churn probability"
+)
+
+interface.launch()