Moved Search into the download model tab

src/webui.py

@@ -193,31 +193,6 @@ if __name__ == '__main__':
         gr.Label('AICoverGen WebUI created with ❤️', show_label=False)
         gr.Markdown("Duplicate this space for use in private: [![Duplicate this Space](https://huggingface.co/datasets/huggingface/badges/raw/main/duplicate-this-space-sm-dark.svg)](https://huggingface.co/spaces/SpyCoder77/AICoverGen?duplicate=true)\n\n") 
 
-        with gr.Tab("Search"):
-            gr.Markdown("# Model Search")
-    
-            with gr.Column():
-                with gr.Row():
-                    query_input = gr.Textbox(
-                        label="Search Query",
-                        placeholder="Enter model name or keyword...",
-                        lines=1,
-                        min_width=320
-                    )
-            
-                with gr.Row():
-                    output_df = gr.Dataframe(
-                        headers=["name", "author", "downloads", "downloadURL"],
-                        datatype=["str", "str", "number", "str"],
-                        row_count=5,
-                        col_count=(4, "fixed"),
-                    )
-
-            query_input.input(
-                fn=filter_records,
-                inputs=query_input,
-                outputs=output_df
-            )
 
             
         with gr.Tab("Generate"):
@@ -318,32 +293,31 @@ if __name__ == '__main__':
                     cache_examples=False,
                 )
 
-            with gr.Tab('From Public Index'):
-
-                gr.Markdown('## How to use')
-                gr.Markdown('- Click Initialize public models table')
-                gr.Markdown('- Filter models using tags or search bar')
-                gr.Markdown('- Select a row to autofill the download link and model name')
-                gr.Markdown('- Click Download')
-
-                with gr.Row():
-                    pub_zip_link = gr.Text(label='Download link to model')
-                    pub_model_name = gr.Text(label='Model name')
-
-                with gr.Row():
-                    download_pub_btn = gr.Button('Download 🌐', variant='primary', scale=19)
-                    pub_dl_output_message = gr.Text(label='Output Message', interactive=False, scale=20)
-
-                filter_tags = gr.CheckboxGroup(value=[], label='Show voice models with tags', choices=[])
-                search_query = gr.Text(label='Search')
-                load_public_models_button = gr.Button(value='Initialize public models table', variant='primary')
-
-                public_models_table = gr.DataFrame(value=[], headers=['Model Name', 'Description', 'Credit', 'URL', 'Tags'], label='Available Public Models', interactive=False)
-                public_models_table.select(pub_dl_autofill, inputs=[public_models_table], outputs=[pub_zip_link, pub_model_name])
-                load_public_models_button.click(load_public_models, outputs=[public_models_table, filter_tags])
-                search_query.change(filter_models, inputs=[filter_tags, search_query], outputs=public_models_table)
-                filter_tags.change(filter_models, inputs=[filter_tags, search_query], outputs=public_models_table)
-                download_pub_btn.click(download_online_model, inputs=[pub_zip_link, pub_model_name], outputs=pub_dl_output_message)
+            with gr.Tab("Search"):
+                gr.Markdown("# Model Search")
+    
+                with gr.Column():
+                    with gr.Row():
+                        query_input = gr.Textbox(
+                            label="Search Query",
+                            placeholder="Enter model name or keyword...",
+                            lines=1,
+                            min_width=320
+                        )
+            
+                    with gr.Row():
+                        output_df = gr.Dataframe(
+                            headers=["name", "author", "downloads", "downloadURL"],
+                            datatype=["str", "str", "number", "str"],
+                            row_count=5,
+                            col_count=(4, "fixed"),
+                        )
+
+                query_input.input(
+                    fn=filter_records,
+                    inputs=query_input,
+                    outputs=output_df
+                )
 
         # Upload tab
         with gr.Tab('Upload model'):