Create app.py

app.py

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+import joblib
+import pandas as pd
+import gradio as gr
+
+# Load model
+model = joblib.load("stroke_rf_model.pkl")
+
+# Define prediction function
+def predict_stroke(age, hypertension, heart_disease, glucose_level, bmi):
+    data = {
+        'age': [age],
+        'hypertension': [hypertension],
+        'heart_disease': [heart_disease],
+        'avg_glucose_level': [glucose_level],
+        'bmi': [bmi]
+    }
+    df = pd.DataFrame(data)
+    prediction = model.predict(df)
+    return "Stroke Risk" if prediction[0] == 1 else "No Stroke Risk"
+
+# Create Gradio Interface
+iface = gr.Interface(
+    fn=predict_stroke,
+    inputs=[
+        gr.Number(label="Age"),
+        gr.Radio(choices=[0, 1], label="Hypertension (0=No, 1=Yes)"),
+        gr.Radio(choices=[0, 1], label="Heart Disease (0=No, 1=Yes)"),
+        gr.Number(label="Average Glucose Level"),
+        gr.Number(label="BMI")
+    ],
+    outputs="text",
+    title="Stroke Prediction Model",
+    description="Predict stroke risk based on health metrics."
+)
+
+# Launch the app
+iface.launch()