Update app.py

app.py

@@ -18,7 +18,7 @@ def formatted_number_input2(title, hint, minval, maxval, defvalue, steps, valfor
 
     st.markdown('<div style="margin-bottom:4px;">', unsafe_allow_html=True)
     
-    col1, col2 = st.columns([3, 1], vertical_alignment="center")
+    col1, col2 = st.columns([2.5, 1], vertical_alignment="center")
     
     with col1:
         st.markdown(
@@ -78,133 +78,141 @@ st.write("Fill in the details below and click **Predict** to see if the Engine n
 # ====================================
 st.subheader ("Engine Parameters")
 
-rpm = formatted_number_input2(
-    "Lubricating oil pressure in kilopascals (kPa)",
-    "50 to 2500",
-    minval=50.0,
-    maxval=2500.0,
-    defvalue=735.0,
-    steps=10.0,
-    valformat="%.2f"
-)
-
-
-oil_pressure = formatted_number_input2(
-    "Lubricating oil pressure in kilopascals (kPa)",
-    "0.001 to 10.0",
-    minval=0.001,
-    maxval=10.0,
-    defvalue=3.300000,
-    steps=0.001,
-    valformat="%.6f"
-)
-
-
-fuel_pressure = formatted_number_input2(
-    "Fuel Pressure in kilopascals (kPa)",
-    "0.01 to 25.0",
-    minval=0.01,
-    maxval=25.0,
-    defvalue=6.500000,
-    steps=0.01,
-    valformat="%.6f"
-)
-
-
-coolant_pressure = formatted_number_input2(
-    "Coolant Pressure in kilopascals (kPa)",
-    "0.01 to 10.0",
-    minval=0.01,
-    maxval=10.0,
-    defvalue=2.250000,
-    steps=0.10,
-    valformat="%.6f"
-)
-
+col_left, col_right = st.columns([1,1])
 
-lub_oil_temp = formatted_number_input2(
-    "Lubricating oil Temperature in degrees Celsius (°C)",
-    "50.0 to 100.0",
-    minval=50.0,
-    maxval=100.0,
-    defvalue=75.0,
-    steps=0.1,
-    valformat="%.6f"
-)
+with col_left:
 
+    rpm = formatted_number_input2(
+        "Lubricating oil pressure in kilopascals (kPa)",
+        "50 to 2500",
+        minval=50.0,
+        maxval=2500.0,
+        defvalue=735.0,
+        steps=10.0,
+        valformat="%.2f"
+    )
+    
+    
+    oil_pressure = formatted_number_input2(
+        "Lubricating oil pressure in kilopascals (kPa)",
+        "0.001 to 10.0",
+        minval=0.001,
+        maxval=10.0,
+        defvalue=3.300000,
+        steps=0.001,
+        valformat="%.6f"
+    )
+    
+    
+    fuel_pressure = formatted_number_input2(
+        "Fuel Pressure in kilopascals (kPa)",
+        "0.01 to 25.0",
+        minval=0.01,
+        maxval=25.0,
+        defvalue=6.500000,
+        steps=0.01,
+        valformat="%.6f"
+    )
 
-coolant_temp = formatted_number_input2(
-    "Coolant Temperature in degrees Celsius (°C)",
-    "50.0 to 200.0",
-    minval=50.0,
-    maxval=200.0,
-    defvalue=75.000000,
-    steps=0.1,
-    valformat="%.6f"
-)
-
-
-# ==========================
-# Single Value Prediction
-# ==========================
-if st.button("Check fo Maintenance"):
-
-    # extract the data collected into a structure
-    input_data = {
-        'Engine_rpm'              : float(rpm),
-        'Lub_oil_pressure'        : float(oil_pressure),
-        'Fuel_pressure'           : float(fuel_pressure),
-        'Coolant_pressure'        : float(coolant_pressure),
-        'lub_oil_temp'            : float(lub_oil_temp),
-        'Coolant_temp'            : float(coolant_temp),
-    }
-
-    input_df = pd.DataFrame([input_data])
+with col_right:
+    coolant_pressure = formatted_number_input2(
+        "Coolant Pressure in kilopascals (kPa)",
+        "0.01 to 10.0",
+        minval=0.01,
+        maxval=10.0,
+        defvalue=2.250000,
+        steps=0.10,
+        valformat="%.6f"
+    )
+    
+    
+    lub_oil_temp = formatted_number_input2(
+        "Lubricating oil Temperature in degrees Celsius (°C)",
+        "50.0 to 100.0",
+        minval=50.0,
+        maxval=100.0,
+        defvalue=75.0,
+        steps=0.1,
+        valformat="%.6f"
+    )
+    
+    
+    coolant_temp = formatted_number_input2(
+        "Coolant Temperature in degrees Celsius (°C)",
+        "50.0 to 200.0",
+        minval=50.0,
+        maxval=200.0,
+        defvalue=75.000000,
+        steps=0.1,
+        valformat="%.6f"
+    )
 
-    response = requests.post (
-        "https://harishsohani-AIMLProjectTestBackEnd.hf.space/v1/EngPredMaintenance",
-        json=input_data
-        )
+st.markdown("---")
 
-    if response.status_code == 200:
-        ## get result as json
-        result = response.json ()
+col_btn1, col_btn2, col_btn3 = st.columns([1,2,1])
 
-        resp_status = result.get ("status")
-
-        if resp_status == "success":
-            
-            ## Get Sales Prediction Value
-            prediction_from_backend = result.get ("prediction")  # Extract only the value
+with col_btn2:
+    # ==========================
+    # Single Value Prediction
+    # ==========================
+    if st.button("Check fo Maintenance"):
+    
+        # extract the data collected into a structure
+        input_data = {
+            'Engine_rpm'              : float(rpm),
+            'Lub_oil_pressure'        : float(oil_pressure),
+            'Fuel_pressure'           : float(fuel_pressure),
+            'Coolant_pressure'        : float(coolant_pressure),
+            'lub_oil_temp'            : float(lub_oil_temp),
+            'Coolant_temp'            : float(coolant_temp),
+        }
+    
+        input_df = pd.DataFrame([input_data])
+    
+        response = requests.post (
+            "https://harishsohani-AIMLProjectTestBackEnd.hf.space/v1/EngPredMaintenance",
+            json=input_data
+            )
+    
+        if response.status_code == 200:
+            ## get result as json
+            result = response.json ()
     
-            # generate output string
-            if prediction_from_backend == 1:
-                resultstr = "Engine **likely** needs maintenance."
+            resp_status = result.get ("status")
+    
+            if resp_status == "success":
+                
+                ## Get Sales Prediction Value
+                prediction_from_backend = result.get ("prediction")  # Extract only the value
+        
+                # generate output string
+                if prediction_from_backend == 1:
+                    resultstr = "Engine **likely** needs maintenance."
+                else:
+                    resultstr = "Engine does not need any maintenance"
+        
+                st.success(resultstr)
+                
             else:
-                resultstr = "Engine does not need any maintenance"
     
-            st.success(resultstr)
+                error_str = result.get ("message")
+    
+                st.error(error_str)
+    
+        elif response.status_code == 400 or response.status_code == 500:  # known errors
             
-        else:
-
+            ## get result as json
+            result = response.json ()
+    
             error_str = result.get ("message")
-
-            st.error(error_str)
-
-    elif response.status_code == 400 or response.status_code == 500:  # known errors
-        
-        ## get result as json
-        result = response.json ()
-
-        error_str = result.get ("message")
-        st.error (f"Error processing request- Status Code : {response.status_code}, error : {error_str}")
-        
-    else:
-        st.error (f"Error processing request- Status Code : {response.status_code}")
-
-    # Show the etails of data frame prepared from user input
-    st.subheader("📦 Input Data Summary")
-    st.dataframe (input_df)
+            st.error (f"Error processing request- Status Code : {response.status_code}, error : {error_str}")
+            
+        else:
+            st.error (f"Error processing request- Status Code : {response.status_code}")
+    
+        # Show the etails of data frame prepared from user input
+        st.subheader("📦 Input Data Summary")
+        st.dataframe (input_df)
 
 
 # ==============================