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app.py

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+import gradio as gr
+import joblib
+import pandas as pd
+import numpy as np
+
+# Define prediction function
+def make_prediction(
+    gender, SeniorCitizen, Partner, Dependents, tenure, PhoneService,
+    MultipleLines, InternetService, OnlineSecurity, OnlineBackup,
+    DeviceProtection, TechSupport, StreamingTV, StreamingMovies,
+    Contract, PaperlessBilling, PaymentMethod,
+    MonthlyCharges, TotalCharges):
+
+
+    # Make a dataframe from input data
+    input_data = pd.DataFrame({
+        'gender': [gender], 'SeniorCitizen': [SeniorCitizen], 'Partner': [Partner],
+        'Dependents': [Dependents], 'tenure': [tenure], 'PhoneService': [PhoneService],
+        'MultipleLines': [MultipleLines], 'InternetService': [InternetService],
+        'OnlineSecurity': [OnlineSecurity], 'OnlineBackup': [OnlineBackup],
+        'DeviceProtection': [DeviceProtection], 'TechSupport': [TechSupport],
+        'StreamingTV': [StreamingTV], 'StreamingMovies': [StreamingMovies],
+        'Contract': [Contract], 'PaperlessBilling': [PaperlessBilling],
+        'PaymentMethod': [PaymentMethod], 'MonthlyCharges': [MonthlyCharges],
+        'TotalCharges': [TotalCharges]
+    })
+
+    # Load already saved pipeline and make predictions
+    with open("preprocessor.joblib", "rb") as p:
+        preprocessor = joblib.load(p)
+        input_data = preprocessor.transform(input_data)
+        # You may need to update this part to drop the relevant columns for your model
+        input_data = input_data.drop(['encode__PaperlessBilling_No', 'encode__MultipleLines_No', 'encode__InternetService_Fiber optic', 'encode__StreamingMovies_No internet service', 'encode__InternetService_No', 'encode__OnlineBackup_No internet service', 'encode__StreamingTV_No internet service'], axis=1)
+
+    # Load already saved pipeline and make predictions
+    with open("rf_model.joblib", "rb") as f:
+        model = joblib.load(f)
+        predt = model.predict(input_data)
+
+    
+    # Return prediction
+    if np.any(predt == 1):
+        return 'Customer Will Churn'
+    else:
+        return 'Customer Will Not Churn'
+
+
+# Create the input components for Gradio with labels
+gender_input = gr.Dropdown(choices=['Female', 'Male'], label='Select gender')
+SeniorCitizen_input = gr.Dropdown(choices=['Yes', 'No'], label='Is the customer a senior citizen?')
+Partner_input = gr.Dropdown(choices=['Yes', 'No'], label='Has the customer a partner?')
+Dependents_input = gr.Dropdown(choices=['Yes', 'No'], label='Does the customer have dependents?')
+tenure_input = gr.Number(label='Number of months the customer has stayed with the company')
+PhoneService_input = gr.Dropdown(choices=['Yes', 'No'], label='Does the customer have phone service?')
+MultipleLines_input = gr.Dropdown(choices=['No phone service', 'No', 'Yes'], label='Does the customer have multiple phone lines?')
+InternetService_input = gr.Dropdown(choices=['DSL', 'Fiber optic', 'No'], label='Type of Internet service')
+OnlineSecurity_input = gr.Dropdown(choices=['No', 'Yes', 'No internet service'], label='Does the customer have online security?')
+OnlineBackup_input = gr.Dropdown(choices=['Yes', 'No', 'No internet service'], label='Does the customer have online backup?')
+DeviceProtection_input = gr.Dropdown(choices=['No', 'Yes', 'No internet service'], label='Does the customer have device protection?')
+TechSupport_input = gr.Dropdown(choices=['No', 'Yes', 'No internet service'], label='Does the customer have tech support?')
+StreamingTV_input = gr.Dropdown(choices=['No', 'Yes', 'No internet service'], label='Does the customer have streaming TV?')
+StreamingMovies_input = gr.Dropdown(choices=['No', 'Yes', 'No internet service'], label='Does the customer have streaming movies?')
+Contract_input = gr.Dropdown(choices=['Month-to-month', 'One year', 'Two year'], label='Type of contract')
+PaperlessBilling_input = gr.Dropdown(choices=['Yes', 'No'], label='Is the customer using paperless billing?')
+PaymentMethod_input = gr.Dropdown(choices=['Electronic check', 'Mailed check', 'Bank transfer (automatic)', 'Credit card (automatic)'], label='Payment method')
+MonthlyCharges_input = gr.Number(label='Monthly charges')
+TotalCharges_input = gr.Number(label='Total charges')
+
+output = gr.Textbox(label='Prediction')
+
+# Set the title of the Gradio app
+app = gr.Interface(fn=make_prediction, inputs=[
+    gender_input, SeniorCitizen_input, Partner_input, Dependents_input, tenure_input,
+    PhoneService_input, MultipleLines_input, InternetService_input, OnlineSecurity_input,
+    OnlineBackup_input, DeviceProtection_input, TechSupport_input, StreamingTV_input,
+    StreamingMovies_input, Contract_input, PaperlessBilling_input, PaymentMethod_input,
+    MonthlyCharges_input, TotalCharges_input], outputs=output, title='Customer Churn Prediction App')
+
+app.launch(share=True, debug=True)

rf_model.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2caf44776f121e5e584125d07ccc7e8853ee30a26a6b3f255542daf3a0341a6b
+size 46576698