app.py

import gradio as gr
from main_func import *

title = "# DeepDR Web Server"

with gr.Blocks() as demo:
    gr.Markdown(title)
    gr.Markdown("Inference using the trained model.")

    with gr.Row():
        with gr.Column():
            with gr.Row():
                with gr.Column():
                    cell_name = gr.Textbox(value='CAL120', label="Cell name", interactive=True)
                    drug_name = gr.Textbox(value='Afuresertib', label="Drug name", interactive=True)
                model_file = gr.File(label="Trained model")

            with gr.Row():
                clear = gr.Button("Clear output", elem_classes="clear")
                submit = gr.Button("Start inference", elem_classes="submit")
            response = gr.Textbox(label="Predicted drug response", interactive=False)

        with gr.Column():
            pair_input = gr.Radio(['CCLE (ActArea)', 'CCLE (IC50)', 'GDSC1 (AUC)', 'GDSC1 (IC50)',
                                   'GDSC2 (AUC)', 'GDSC2 (IC50)'],
                                  label="Dataset", value='CCLE (ActArea)', interactive=False)
            with gr.Row():
                cell_input = gr.Radio(['EXP', 'PES', 'MUT', 'CNV'], label="Cell feature", value='EXP')
                drug_input = gr.Radio(['FP', 'SMILES', 'Graph', 'Img'], label="Drug feature", value='Graph')
                split_mode = gr.Radio(['Rand', 'Cell', 'Drug', 'Strict'],
                                      label="Splitting", value='Cell', interactive=False)
            gr.Examples([
                ['model1.pkl', 'CCLE (ActArea)', 'Cell', 'EXP', 'Graph']
            ], inputs=[model_file, pair_input, split_mode, cell_input, drug_input], label="Example")

    submit.click(fn=func2, inputs=[cell_name, drug_name, model_file, cell_input, drug_input],
                 outputs=[response])
    clear.click(fn=clear_func2, inputs=[], outputs=[response])

demo.launch(favicon_path="IC50.png")