Update app.py

app.py

@@ -1,4 +1,46 @@
 import streamlit as st
+import pandas as pd
+import joblib
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+# Load the saved model
+loaded_model = joblib.load('diabetes_prediction_model.joblib')
+
+def predict_diabetes(data):
+    # Use the loaded model to make predictions
+    predicted_class = loaded_model.predict(data)
+    return predicted_class
+
+def main():
+    st.title("Diabetes Prediction App")
+
+    # Create input form for user to enter values
+    st.sidebar.header("User Input Features")
+
+    pregnancies = st.sidebar.slider("Pregnancies", 0, 17, 3)
+    glucose = st.sidebar.slider("Glucose", 0, 199, 117)
+    blood_pressure = st.sidebar.slider("Blood Pressure", 0, 122, 72)
+    skin_thickness = st.sidebar.slider("Skin Thickness", 0, 99, 23)
+    insulin = st.sidebar.slider("Insulin", 0, 846, 30)
+    bmi = st.sidebar.slider("BMI", 0.0, 67.1, 32.0)
+    diabetes_pedigree_function = st.sidebar.slider("Diabetes Pedigree Function", 0.078, 2.42, 0.3725)
+    age = st.sidebar.slider("Age", 21, 81, 29)
+
+    # Create a DataFrame from user input
+    user_data = pd.DataFrame({
+        'Pregnancies': [pregnancies],
+        'Glucose': [glucose],
+        'BloodPressure': [blood_pressure],
+        'SkinThickness': [skin_thickness],
+        'Insulin': [insulin],
+        'BMI': [bmi],
+        'DiabetesPedigreeFunction': [diabetes_pedigree_function],
+        'Age': [age]
+    })
+
+    # Make prediction
+    if st.button("Predict"):
+        prediction = predict_diabetes(user_data)
+        st.success(f"The individual is {'Diabetic' if prediction[0] == 1 else 'Not Diabetic'}.")
+
+if __name__ == "__main__":
+    main()