Upload app.py

app.py

@@ -36,12 +36,30 @@ def process_excel(file):
     soil_data = np.stack([x_train, bh2, data_pile], axis=2)
     return soil_data
 
+def validate_inputs(pile_length, section_width, section_length, pile_type):
+    if pile_length < 39 or pile_length > 60:
+        return False, "Pile length must be between 39 and 60 meters."
+    
+    if pile_type == "Circular":
+        if section_width < 0.8 or section_width > 1.8 or section_length < 0.8 or section_length > 1.8:
+            return False, "For circular piles, section width and length must be between 0.8 and 1.8 meters."
+    elif pile_type == "Barrette":
+        if section_width < 1 or section_width > 4 or section_length < 1 or section_length > 4:
+            return False, "For barrette piles, section width and length must be between 1 and 4 meters."
+    
+    return True, ""
+
 def predict_pile(file_choice, uploaded_file, pile_length, section_width, section_length, pile_type):
+    # Validate inputs
+    is_valid, error_message = validate_inputs(pile_length, section_width, section_length, pile_type)
+    if not is_valid:
+        return None, error_message
+
     if file_choice == "default":
         file = "default"
     else:
         if uploaded_file is None:
-            return "Please upload an Excel file or choose the default option."
+            return None, "Please upload an Excel file or choose the default option."
         file = uploaded_file
     
     X = process_excel(file)
@@ -83,13 +101,13 @@ def predict_pile(file_choice, uploaded_file, pile_length, section_width, section
     plt.xlabel("Deformation (mm)")
     plt.ylabel("Load (kN)")
     plt.title(f"Pile Prediction (Length: {pile_length}m, {pile_type})")
-    return plt
+    return plt, ""
 
 def update_file_input(choice):
     return gr.update(visible=choice == "upload")
 
 with gr.Blocks() as iface:
-    gr.Markdown("# Pile Prediction Model")
+    gr.Markdown("# Pile Prediction Model in Bangkok Subsoil")
     gr.Markdown("Choose the default Excel file or upload your own, then enter pile characteristics to predict pile behavior.")
     
     with gr.Row():
@@ -103,6 +121,7 @@ with gr.Blocks() as iface:
         pile_type = gr.Radio(["Circular", "Barrette"], label="Pile Type", value="Circular")
     
     output = gr.Plot()
+    error_output = gr.Textbox(label="Error", visible=True)
     
     submit_btn = gr.Button("Predict")
     
@@ -118,7 +137,7 @@ with gr.Blocks() as iface:
     submit_btn.click(
         fn=predict_pile,
         inputs=[file_choice, uploaded_file, pile_length, section_width, section_length, pile_type],
-        outputs=[output]
+        outputs=[output, error_output]
     )
 
 iface.launch()