Update app.py

app.py

@@ -166,10 +166,11 @@ def predict_inverse(hardness_target, ys_target, request: gr.Request):
 
     constraints = []
     constrained_columns = ['Single/Multiphase', 'Preprocessing method', 'BCC/FCC/other']#, 'Microstructure']
+    one_hot_colums = utils.return_feature_names()
     for constraint in constrained_columns:
         sum_string = ''
-        for i in range (len(one_hot.columns)):
-            column_one_hot = one_hot.columns[i]
+        for i in range (len(one_hot_columns)):
+            column_one_hot = one_hot_columns[i]
             if column_one_hot.startswith(constraint):
                 sum_string = sum_string+"+x[:," + str(i) + "]"
         constraints.append({'name': constraint + "+1", 'constraint': sum_string + '-1'})
@@ -245,25 +246,6 @@ with gr.Blocks(css=css_styling, title=page_title, theme=osium_theme) as demo:
             input_yield_strength = gr.Text(label="Enter your target yield strength (MPa)")
         with gr.Column():
             gr.Markdown("### Your optimal formulation and processing conditions")
-            output_formula = gr.Textbox(
-                lines=1, label=input_cols["PROPERTY: Alloy formula"]
-            )
-            output_phase = gr.Dropdown(
-                choices=list(input_mapping["PROPERTY: Single/Multiphase"].keys()),
-                label=input_cols["PROPERTY: Single/Multiphase"],
-            )
-            output_bccfcc = gr.Dropdown(
-                choices=list(input_mapping["PROPERTY: BCC/FCC/other"].keys()),
-                label=input_cols["PROPERTY: BCC/FCC/other"],
-            )
-            output_processing = gr.Dropdown(
-                choices=list(input_mapping["PROPERTY: Processing method"].keys()),
-                label=input_cols["PROPERTY: Processing method"],
-            )
-            output_microstructure = gr.CheckboxGroup(
-                choices=unique_phase_elements, #list(input_mapping["PROPERTY: Microstructure"].keys()),
-                label=input_cols["PROPERTY: Microstructure"],
-            )
             optimal_parameters = gr.DataFrame(label="Optimal parameters")
         
         # with gr.Column():