Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import joblib
+
+# Load model
+model = joblib.load('maintenance_model.pkl')
+
+# App UI
+st.title("Smart Maintenance Planner")
+st.sidebar.header("Input Parameters")
+
+# Input form
+def user_input_features():
+    temperature = st.sidebar.number_input("Temperature (°C)")
+    vibration = st.sidebar.number_input("Vibration (mm/s)")
+    pressure = st.sidebar.number_input("Pressure (Pa)")
+    return pd.DataFrame([[temperature, vibration, pressure]], columns=['temperature', 'vibration', 'pressure'])
+
+input_df = user_input_features()
+
+# Predictions
+if st.button('Predict Maintenance Need'):
+    prediction = model.predict(input_df)
+    if prediction[0] == 1:
+        st.error("Maintenance Required!")
+    else:
+        st.success("Unit is functioning normally.")
+
+# Dashboard
+st.subheader("Operational Data Overview")
+# Replace with your data source
+st.dataframe(input_df)