Update app.py

app.py

@@ -45,7 +45,7 @@ def calculate_process_cost(process_type, input_weight):
 # Streamlit interface
 st.title("EX-Works Calculator")
 
-# Create tabs
+# Tabs for page navigation
 tabs = st.tabs(["Home", "Vendor Data", "Material Data", "RM Cost Data", "Supplier Data"])
 
 with tabs[0]:
@@ -80,4 +80,113 @@ with tabs[2]:
     green_drg_no = st.selectbox("Green DRG Number", options=[0, 1])
     
     if st.button("Add Material"):
-        material_data = pd.DataFrame({'Part_id': [part_id], 'part_no': [part_no], 'scf': [scf], 'process_type': [process_type], 'part_od': [part_od], 'part_width': [part_width], 'part_inner_dimension': [part_inner_dimension], 'material_specification': [material_spec], 'finish_wt':
+        material_data = pd.DataFrame({'Part_id': [part_id], 'part_no': [part_no], 'scf': [scf], 'process_type': [process_type], 'part_od': [part_od], 'part_width': [part_width], 'part_inner_dimension': [part_inner_dimension], 'material_specification': [material_spec], 'finish_wt': [finish_wt], 'green_drg_no': [green_drg_no]})
+        insert_data(conn, 'material_data', material_data)
+        st.success("Material data added successfully")
+
+with tabs[3]:
+    st.header("RM Cost Data")
+    rm_type = st.text_input("RM Type")
+    rm_cost = st.number_input("RM Cost", min_value=0.0, step=0.01)
+    vendor_id = st.number_input("Vendor ID", min_value=1, step=1)
+    
+    if st.button("Add RM Cost Data"):
+        rm_cost_data = pd.DataFrame({'rm_type': [rm_type], 'rm_cost': [rm_cost], 'vendor_id': [vendor_id]})
+        insert_data(conn, 'rm_cost_data', rm_cost_data)
+        st.success("RM cost data added successfully")
+
+with tabs[4]:
+    st.header("Supplier Data")
+    part_no = st.number_input("Part No", min_value=1, step=1)
+    process_type = st.selectbox("Process Type", options=[0, 1])
+    part_od = st.number_input("Part OD", min_value=0.0, step=0.1)
+    part_id = st.number_input("Part ID", min_value=0.0, step=0.1)
+    part_width = st.number_input("Part Width", min_value=0, step=1)
+    finish_wt = st.number_input("Finish Wt", min_value=0.0, step=0.1)
+    grade_type = st.selectbox("Grade Type", options=list(final_landed_cost.keys()))
+    material_id = st.number_input("Material ID", min_value=1, step=1)
+    
+    if st.button("Calculate and Add Supplier Data"):
+        # Prepare the input data for prediction
+        input_data = pd.DataFrame({
+            'Process type': [process_type],
+            'Part Od': [part_od],
+            'Part ID': [part_id],
+            'Part Width': [part_width],
+            'Finish Wt': [finish_wt]
+        })
+
+        # Predict the input weight
+        predicted_input_weight = input_weight_model.predict(input_data)[0]
+
+        # Calculate raw material cost
+        raw_material_cost = calculate_raw_material_cost(process_type, predicted_input_weight, grade_type)
+        
+        # Calculate process cost
+        process_cost = calculate_process_cost(process_type, predicted_input_weight)
+        
+        # Prepare the data for machining time prediction
+        machining_data = pd.DataFrame({
+            'Process type': [process_type],
+            'Part Od': [part_od],
+            'Part ID': [part_id],
+            'Part Width': [part_width],
+            'Finish Wt': [finish_wt],
+            'Input Weight': [predicted_input_weight],
+            'Raw material cost': [raw_material_cost],
+            'Process cost': [process_cost]
+        })
+
+        # Predict the machining time
+        predicted_machining_time = machining_model.predict(machining_data)[0]
+
+        # Calculate machining cost
+        machining_cost = predicted_machining_time * 375.71
+        
+        # Calculate scrap recovery
+        scrap_recovery = (predicted_input_weight - finish_wt) * 11.5
+        
+        # Prepare the data for inspection time prediction
+        inspection_data = pd.DataFrame({
+            'Process type': [process_type],
+            'Part Od': [part_od],
+            'Part ID': [part_id],
+            'Part Width': [part_width],
+            'Finish Wt': [finish_wt],
+            'Input Weight': [predicted_input_weight],
+            'Raw material cost': [raw_material_cost],
+            'Process cost': [process_cost],
+            'Machining Time': [predicted_machining_time],
+            'Machining cost': [machining_cost],
+            'Scrap recovery': [scrap_recovery]
+        })
+
+        # Predict the inspection time
+        predicted_inspection_time = inspection_model.predict(inspection_data)[0]
+
+        # Calculate inspection cost
+        inspection_cost = predicted_inspection_time * 375.71
+        
+        # Calculate total manufacturing cost
+        total_mg_cost = raw_material_cost + process_cost + machining_cost - scrap_recovery + inspection_cost
+        
+        # Insert supplier data
+        supplier_data = pd.DataFrame({
+            'Part No': [part_no],
+            'Process Type': [process_type],
+            'Part OD': [part_od],
+            'Part ID': [part_id],
+            'Part Width': [part_width],
+            'Finish Wt': [finish_wt],
+            'Grade Type': [grade_type],
+            'Material ID': [material_id],
+            'Predicted Input Weight': [predicted_input_weight],
+            'Raw Material Cost': [raw_material_cost],
+            'Process Cost': [process_cost],
+            'Machining Cost': [machining_cost],
+            'Scrap Recovery': [scrap_recovery],
+            'Inspection Cost': [inspection_cost],
+            'Total Manufacturing Cost': [total_mg_cost]
+        })
+        insert_data(conn, 'supplier_data', supplier_data)
+        st.success("Supplier data added successfully")