Update app.py

app.py

@@ -1,12 +1,19 @@
 import pandas as pd
 import streamlit as st
 
-# Assuming label_encoders, scaler, and model are defined elsewhere
-# Define label_encoders, scaler, and model here or import them properly
+# Define or import label_encoders, scaler, and model
+# Example:
+from sklearn.preprocessing import LabelEncoder, StandardScaler
+from sklearn.ensemble import RandomForestClassifier
+
+# Assume label_encoders, scaler, and model are defined and fitted elsewhere
+# Initialize label_encoders, scaler, and model
+label_encoders = {}
+scaler = StandardScaler()
+model = RandomForestClassifier(n_estimators=100, random_state=42)
 
 # Function to preprocess input data and predict disease risk
 def predict_disease_risk(input_data):
-    # Convert input_data into a DataFrame for prediction
     input_df = pd.DataFrame({
         'Age': [input_data['Age']],
         'Gender': [input_data['Gender']],
@@ -65,3 +72,4 @@ input_data = {
 if st.button('Predict Disease Risk'):
     prediction = predict_disease_risk(input_data)
     st.write(f'Predicted Disease Risk: {prediction}')
+