Update src/webui.py

src/webui.py

@@ -4,7 +4,6 @@ import shutil
 import urllib.request
 import zipfile
 from argparse import ArgumentParser
-import spaces
 import gradio as gr
 import requests
 
@@ -107,26 +106,19 @@ def upload_local_model(zip_path, dir_name, progress=gr.Progress()):
 def filter_models(tags, query):
     models_table = []
 
-    # no filter
     if len(tags) == 0 and len(query) == 0:
         for model in public_models['voice_models']:
             models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']])
-
-    # filter based on tags and query
     elif len(tags) > 0 and len(query) > 0:
         for model in public_models['voice_models']:
             if all(tag in model['tags'] for tag in tags):
                 model_attributes = f"{model['name']} {model['description']} {model['credit']} {' '.join(model['tags'])}".lower()
                 if query.lower() in model_attributes:
                     models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']])
-
-    # filter based on only tags
     elif len(tags) > 0:
         for model in public_models['voice_models']:
             if all(tag in model['tags'] for tag in tags):
                 models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']])
-
-    # filter based on only query
     else:
         for model in public_models['voice_models']:
             model_attributes = f"{model['name']} {model['description']} {model['credit']} {' '.join(model['tags'])}".lower()
@@ -182,16 +174,17 @@ if __name__ == '__main__':
         )
         gr.Markdown("Duplicate the old CPU 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/r3gm/AICoverGen_old_stable_cpu?duplicate=true)\n\n") 
 
-        # main tab
         with gr.Tab("Find Models"):
-            gr.Textbox(placeholder="Eg: Taylor Swift, Drake", max_lines=1, lines=1)
-                with gr.Row():
-                    with gr.Column(scale=1):
-                        text1 = gr.Textbox()
-                        text2 = gr.Textbox()
-                    with gr.Column(scale=4):
-                        btn1 = gr.Button("Button 1")
-                        btn2 = gr.Button("Button 2")
+            model_query = gr.Textbox(placeholder="Eg: Taylor Swift, Drake", max_lines=1, lines=1)
+            model_display = gr.Dataframe(
+                headers=["name", "author", "url"],
+                datatype=["str", "str", "str"],
+                row_count=5,
+                col_count=(3, "fixed"),
+            )
+            filter_btn = gr.Button("Search")
+            filter_btn.click(lambda query: filter_models([], query), inputs=model_query, outputs=model_display)
+            
         with gr.Tab("Generate"):
             
             with gr.Accordion('Main Options'):
@@ -338,7 +331,6 @@ if __name__ == '__main__':
 
     app.launch(
         share=args.share_enabled,
-        # enable_queue=True,
         server_name=None if not args.listen else (args.listen_host or '0.0.0.0'),
         server_port=args.listen_port,
     )