Upload app.py

app.py

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+import streamlit as st
+import numpy as np
+import joblib
+
+# ✅ Load Model & Scaler from Specific Path
+model_path = ("C:\\Users\\KAUSHIK\\OneDrive\\Documents\\lr.pkl")
+scaler_path = ("C:\\Users\\KAUSHIK\\OneDrive\\Documents\\scaler.pkl")
+
+lr = joblib.load(model_path)
+scaler = joblib.load(scaler_path)
+
+st.title("Diabetes Disease Progression Predictor")
+st.write("Enter the following patient details:")
+
+# Input Features
+features = ['age', 'sex', 'bmi', 'bp', 's1', 's2', 's3', 's4', 's5', 's6']
+inputs = []
+
+for feature in features:
+    val = st.number_input(f"{feature}", value=0.0, step=0.01, format="%.2f")
+    inputs.append(val)
+
+# Predict Button
+if st.button("Predict Disease Progression"):
+    data = np.array([inputs])
+    scaled_data = scaler.transform(data)
+    prediction = lr.predict(scaled_data)
+    st.success(f"Predicted Disease Progression Score: {prediction[0]:.2f}")