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app.py

@@ -16,11 +16,11 @@ st.write("Kindly enter the enging parameters.")
 
 # Get the inputs and save them into a dataframe
 Engine_rpm = st.number_input("Engine rpms", min_value=0, max_value=5000, value=500)
-Lub_oil_pressure = st.number_input("Lub oil pressure(in kPa)", min_value=1, max_value=5, value=3)
-Fuel_pressure = st.number_input("Fuel pressure (in kPa)", min_value=0, max_value=100, value=50)
-Coolant_pressure = st.number_input("Coolant pressure (in kPa)", min_value=0, max_value=50, value=1)
-lub_oil_temp = st.number_input("Lub oil temprature (in °C)", min_value=0, max_value=50, value=1)
-Coolant_temp = st.number_input("Coolant temprature (in °C)", min_value=1, max_value=5, value=3)
+Lub_oil_pressure = st.number_input("Lub oil pressure(in kPa)", min_value=0.0, max_value=20.0, value=3.0,format="%.4f")
+Fuel_pressure = st.number_input("Fuel pressure (in kPa)", min_value=0.0, max_value=20.0, value=3.0,format="%.4f")
+Coolant_pressure = st.number_input("Coolant pressure (in kPa)", min_value=0.0, max_value=20.0, value=1.0,format="%.4f")
+lub_oil_temp = st.number_input("Lub oil temprature (in °C)", min_value=0.0, max_value=100.0, value=70.0,format="%.4f")
+Coolant_temp = st.number_input("Coolant temprature (in °C)", min_value=0.0, max_value=250.0, value=100.0,format="%.4f")
 
 # Save the inputs into a Dataframe. Convert categorical inputs to match model training
 input_data = pd.DataFrame([{