Update app.py

app.py

@@ -261,19 +261,20 @@ For more details, see our [paper on arXiv](https://arxiv.org/abs/2302.07868).
 - **SNN ChEMBL**: Similarity to ChEMBL molecules (higher means more similar to known drug-like compounds)
 - **SNN Real Inhibitors**: Similarity to known drugs (higher means more similar to approved drugs)
         """)
-
+    with gr.Row():
+        with gr.Column(scale=1):
+            model_name = gr.Radio(
+                choices=("DrugGEN-AKT1", "DrugGEN-CDK2", "DrugGEN-NoTarget"),
+                value="DrugGEN-AKT1",
+                label="Select Target Model",
+                info="Choose which protein target or general model to use for molecule generation"
+            )
+            
     # Use Gradio Tabs to separate the two modes.
     with gr.Tabs():
         with gr.TabItem("Classical Generation"):
             with gr.Row():
                 with gr.Column(scale=1):
-                    model_name = gr.Radio(
-                        choices=("DrugGEN-AKT1", "DrugGEN-CDK2", "DrugGEN-NoTarget"),
-                        value="DrugGEN-AKT1",
-                        label="Select Target Model",
-                        info="Choose which protein target or general model to use for molecule generation"
-                    )
-
                     num_molecules = gr.Slider(
                         minimum=10,
                         maximum=200,
@@ -294,25 +295,6 @@ For more details, see our [paper on arXiv](https://arxiv.org/abs/2302.07868).
                         variant="primary",
                         size="lg"
                     )
-                with gr.Column(scale=2):
-                    basic_metrics_df = gr.Dataframe(
-                        headers=["Validity", "Uniqueness", "Novelty (Train)", "Novelty (Inference)", "Novelty (Real Inhibitors)", "Runtime (s)"],
-                        elem_id="basic-metrics"
-                    )
-                        
-                    advanced_metrics_df = gr.Dataframe(
-                        headers=["QED", "SA Score", "Internal Diversity", "SNN (ChEMBL)", "SNN (Real Inhibitors)", "Average Length"],
-                        elem_id="advanced-metrics"
-                    )
-
-                    file_download = gr.File(
-                        label="Download All Generated Molecules (SMILES format)"
-                    )
-                    
-                    image_output = gr.Image(
-                        label="Structures of Randomly Selected Generated Molecules",
-                        elem_id="molecule_display"
-                    )
 
         with gr.TabItem("Custom Input SMILES"):
             with gr.Row():
@@ -334,25 +316,22 @@ For more details, see our [paper on arXiv](https://arxiv.org/abs/2302.07868).
                         variant="primary",
                         size="lg"
                     )
-                with gr.Column(scale=2):
-                    basic_metrics_df_custom = gr.Dataframe(
-                        headers=["Validity", "Uniqueness", "Novelty (Train)", "Novelty (Inference)", "Novelty (Real Inhibitors)", "Runtime (s)"],
-                        elem_id="basic-metrics-custom"
-                    )
+
+    with gr.Column(scale=2):
+        basic_metrics_df = gr.Dataframe(
+            headers=["Validity", "Uniqueness", "Novelty (Train)", "Novelty (Inference)", "Novelty (Real Inhibitors)", "Runtime (s)"],
+            elem_id="basic-metrics"
+        )
                         
-                    advanced_metrics_df_custom = gr.Dataframe(
-                        headers=["QED", "SA Score", "Internal Diversity", "SNN (ChEMBL)", "SNN (Real Inhibitors)", "Average Length"],
-                        elem_id="advanced-metrics-custom"
-                    )
+        advanced_metrics_df = gr.Dataframe(
+            headers=["QED", "SA Score", "Internal Diversity", "SNN (ChEMBL)", "SNN (Real Inhibitors)", "Average Length"],
+            elem_id="advanced-metrics"
+        )
 
-                    file_download_custom = gr.File(
-                        label="Download All Molecules (SMILES format)"
-                    )
+        file_download = gr.File(label="Download All Generated Molecules (SMILES format)")
                     
-                    image_output_custom = gr.Image(
-                        label="Structures of Randomly Selected Molecules",
-                        elem_id="molecule_display_custom"
-                    )
+        image_output = gr.Image(label="Structures of Randomly Selected Generated Molecules",
+                        elem_id="molecule_display")
 
     gr.Markdown("### Created by the HUBioDataLab | [GitHub](https://github.com/HUBioDataLab/DrugGEN) | [Paper](https://arxiv.org/abs/2302.07868)")