Create app.py

app.py

@@ -0,0 +1,19 @@
+import gradio as gr
+from model_list import ModelList
+model_list = ModelList()
+with gr.Blocks(css=css) as demo:   
+            with gr.Row():
+                gr.Image(value="RAII.svg",scale=1,show_download_button=False,show_share_button=False,show_label=False,height=100,container=False) 
+                gr.Markdown("# Models for Healthcare Teams")
+            search_box = gr.Textbox(label='Search Name',placeholder='You can search for titles with regular expressions. e.g. (?<!sur)face',max_lines=1)
+            case_sensitive = gr.Checkbox(label='Case Sensitive')
+            filter_names1 = gr.CheckboxGroup(choices=['NLP','Computer Vision', 'Multi-Model'], value=['NLP','Computer Vision', 'Multi-Model'], label='Task')
+            data_type_names1 = ['Biomedical Corpus','Scientific Corpus','Clinical Corpus','Image','Mixed']
+            data_types1 = gr.CheckboxGroup(choices=data_type_names1, value=data_type_names1, label='Training Data Type')
+            search_button = gr.Button('Search')
+            table = gr.HTML(show_label=False)
+            demo.load(fn=model_list.render, inputs=[search_box, case_sensitive, filter_names1, data_types1,],outputs=[table,])
+            search_box.submit(fn=model_list.render, inputs=[search_box, case_sensitive, filter_names1, data_types1,], outputs=[table,])
+            search_button.click(fn=model_list.render, inputs=[search_box, case_sensitive, filter_names1, data_types1,], outputs=[table,])
+demo.queue()
+demo.launch(share=False)