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| #!/usr/bin/env python | |
| from __future__ import annotations | |
| import gradio as gr | |
| from model_list import ModelList | |
| DESCRIPTION = '# Explore Biomedical Language Models' | |
| NOTES = ''' | |
| - Stanford HAI Article, ["The Shaky Foundations of Foundation Models in Healthcare"](https://hai.stanford.edu/news/shaky-foundations-foundation-models-healthcare) | |
| ''' | |
| FOOTER = '''''' | |
| def main(): | |
| model_list = ModelList() | |
| with gr.Blocks(css='style.css') as demo: | |
| gr.Markdown(DESCRIPTION) | |
| search_box = gr.Textbox( | |
| label='Search Model 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_names = gr.CheckboxGroup(choices=[ | |
| 'Paper', | |
| 'Code', | |
| 'Model Weights', | |
| ], label='Filter') | |
| data_type_names = [ | |
| 'Biomedical', | |
| 'Clinical', | |
| 'Scientific', | |
| ] | |
| data_types = gr.CheckboxGroup(choices=data_type_names, | |
| value=data_type_names, | |
| label='Training Data Type(s)') | |
| search_button = gr.Button('Search') | |
| number_of_models = gr.Textbox(label='Number of Models Found') | |
| table = gr.HTML(show_label=False) | |
| gr.Markdown(NOTES) | |
| gr.Markdown(FOOTER) | |
| demo.load(fn=model_list.render, | |
| inputs=[ | |
| search_box, | |
| case_sensitive, | |
| filter_names, | |
| data_types, | |
| ], | |
| outputs=[ | |
| number_of_models, | |
| table, | |
| ]) | |
| search_box.submit(fn=model_list.render, | |
| inputs=[ | |
| search_box, | |
| case_sensitive, | |
| filter_names, | |
| data_types, | |
| ], | |
| outputs=[ | |
| number_of_models, | |
| table, | |
| ]) | |
| search_button.click(fn=model_list.render, | |
| inputs=[ | |
| search_box, | |
| case_sensitive, | |
| filter_names, | |
| data_types, | |
| ], | |
| outputs=[ | |
| number_of_models, | |
| table, | |
| ]) | |
| demo.launch(enable_queue=True, share=False) | |
| if __name__ == '__main__': | |
| main() | |