app.py

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)