| # first layer extraction(text) | |
| # second layer extraction(first layer output) | |
| # third layer extraction(first layer outputs aggregated, second layer outputs aggregated) | |
| # fourth layer extraction(first layer output, second layer output, third layer output) | |
| import gradio as gr | |
| from cloud_db import * | |
| from supplier import * | |
| from utility import * | |
| from features import init_app_data | |
| from ui_device import * | |
| from ui_equivalent import * | |
| examples = [] | |
| # app_theme = gr.themes.Base(neutral_hue="blue") | |
| demo = gr.TabbedInterface( | |
| [device_page,equivalent_page], | |
| ["Device","Equivalent Comparators"], | |
| theme = gr.themes.Soft(primary_hue="sky",secondary_hue="orange"), | |
| title="AMRA AI Medi Reader", | |
| css = "footer {visibility: hidden}", | |
| ) | |
| # ) | |
| def refresh_data(): | |
| return | |
| if __name__ == "__main__": | |
| init_app_data() | |
| demo.launch() |