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import gradio as gr
import pandas as pd
def topn_tokens(sequence, domain_bounds, n):
example_dict = {}
chars = list(sequence)
start_index = domain_bounds['start'][0] - 1
end_index = domain_bounds['end'][0] - 1
for i in range(len(sequence)):
if start_index <= i <= end_index:
example_dict[chars[i]] = 'yo'
df = pd.DataFrame(list(example_dict.items()), columns=['Original Residue', 'Predicted Residues'])
return df
demo = gr.Interface(
fn=topn_tokens,
inputs=[
"text",
gr.Dataframe(
headers=["start", "end"],
datatype=["number", "number"],
row_count=(1, "fixed"),
col_count=(2, "fixed"),
),
gr.Dropdown([str(i) for i in range(1, 21)]), # Dropdown with numbers from 1 to 20
],
outputs="dataframe",
description="Choose a number between 1-20 to predict n tokens for each position. Choose the start and end index of the domain of interest (indexing starts at 1).",
)
if __name__ == "__main__":
demo.launch()
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