Update app.py

app.py

@@ -158,7 +158,7 @@ with col_inputs:
             
             
             oil_pressure = formatted_number_input(
-                "Lubricating oil pressure (kPa)",
+                "Lubricating oil pressure in kPa",
                 "0.001 to 10.0",
                 minval=0.001,
                 maxval=10.0,
@@ -169,7 +169,7 @@ with col_inputs:
             
             
             fuel_pressure = formatted_number_input(
-                "Fuel Pressure (kPa)",
+                "Fuel Pressure in kPa",
                 "0.01 to 25.0",
                 minval=0.01,
                 maxval=25.0,
@@ -181,7 +181,7 @@ with col_inputs:
         # define inputs in left column
         with col_right:
             coolant_pressure = formatted_number_input(
-                "Coolant Pressure (kPa)",
+                "Coolant Pressure in kPa",
                 "0.01 to 10.0",
                 minval=0.01,
                 maxval=10.0,
@@ -192,7 +192,7 @@ with col_inputs:
             
             
             lub_oil_temp = formatted_number_input(
-                "Lubricating oil Temperature (°C)",
+                "Lubricating oil Temperature in °C",
                 "50.0 to 100.0",
                 minval=50.0,
                 maxval=100.0,
@@ -203,7 +203,7 @@ with col_inputs:
             
             
             coolant_temp = formatted_number_input(
-                "Coolant Temperature (°C)",
+                "Coolant Temperature in °C",
                 "50.0 to 200.0",
                 minval=50.0,
                 maxval=200.0,
@@ -212,7 +212,7 @@ with col_inputs:
                 valformat="%.6f"
             )
 
-        submitted = st.form_submit_button("🚀 Check for Maintenance")
+        submitted = st.form_submit_button("🚀 Check Maintenance")
 
 
 with col_output:
@@ -307,12 +307,12 @@ st.markdown("---")
 
 st.subheader ("Batch Prediction for Engine Maintenance")
 st.markdown("""
-*Select csv file engine sensor parameters to find prediction for all readings*
+*Select csv file with engine sensor parameters to find prediction for all readings*
 """)
 
 file = st.file_uploader ("Upload CSV file", type=["csv"])
 
-if file is not None and st.button("Predict Batch"):
+if file is not None and st.button("🚀 Check Maintenance"):
 
     inputfile = {"file": (file.name, file.getvalue(), "text/csv")}
     response = requests.post(
@@ -345,6 +345,11 @@ if file is not None and st.button("Predict Batch"):
                 input_df["Probability"] = probabilities
     
                 st.success("Batch prediction completed successfully")
+
+                st.markdown("""
+                *Prediction  : 1 deontes Maintenance is needed*
+                *Probability : Indicates failure probability and value ranges from 0.0 to 1.0. Value of 0.5 (50%) and above is suggested for Maintenance*
+                """)
     
                 # Show combined dataframe
                 st.dataframe(input_df, use_container_width=True)