import gradio as gr | |
from gradio_cofoldinginput import CofoldingInput | |
import json | |
def predict(input): | |
input = json.dumps(input) | |
return input | |
with gr.Blocks() as demo: | |
jobname = gr.Textbox(label="Job Name") | |
inp=CofoldingInput(label="Input") | |
preinput = {"chains": [ | |
{ | |
"class": "DNA", | |
"sequence": "ATGCGT", | |
"chain": "A" | |
}, | |
{ | |
"class": "protein", | |
"sequence": "AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA", | |
"chain": "B" | |
}, | |
{ | |
"class": "ligand", | |
"name": "ZN", | |
"smiles": "", | |
"sdf": "", | |
"chain": "C" | |
}, | |
{ | |
"class": "ligand", | |
"smiles": "CCCCCCCCCCCCCCCCCCCC", | |
"name": "", | |
"sdf": "", | |
"chain": "D" | |
} | |
], "covMods":[] | |
} | |
# inp2=CofoldingInput(preinput, label="Input prefilled") | |
btn = gr.Button("Submit") | |
out = gr.HTML() | |
gr.Examples([["test",preinput]], inputs=[jobname,inp]) | |
btn.click(predict, inputs=[inp], outputs=[out]) | |
if __name__ == "__main__": | |
demo.launch() | |