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from io import StringIO
import gradio as gr
import pandas as pd
import spacy
nlp = spacy.load('en_core_web_sm')
HTML_RED = '<span style="background-color: rgba(255, 0, 0, 0.2)">{t}</span>'
HTML_GRN = '<span style="background-color: rgba(0, 255, 0, 0.3)">{t}</span>'
HTML_BLU = '<span style="background-color: rgba(0, 0, 255, 0.2)">{t}</span>'
HTML_PLN = '<span>{t}</span>'
TABLE_CSS = '''
th, td {
padding: 4px;
}
table, th, td {
border: 1px solid black;
border-collapse: collapse;
}
'''
def colorize(file_obj):
with open(file_obj.name, 'r') as f:
raw = f.read()
raw = raw[raw.find('example_id'):]
data = pd.read_csv(StringIO(raw))
table_content = []
for row in data.iterrows():
id_ = row[1]['example_id']
gold, genA, genB = nlp.pipe((
row[1]['target summary'],
row[1]['model summary A'],
row[1]['model summary B']
))
tokens_gold = {token.lemma_.lower() for token in gold}
table_content.append(
[id_, gold.text] +
[
''.join(
(
HTML_PLN.format(t=token.text)
if token.pos_ not in {'NOUN', 'PROPN', 'VERB'}
else (
HTML_GRN.format(t=token.text)
if token.lemma_.lower() in tokens_gold
else HTML_RED.format(t=token.text)
)
) + token.whitespace_
for token in gen
)
for gen in (genA, genB)
]
)
# return an HTML table using data in table_content
return '\n'.join((
'<table>',
"<tr>"
"<td><b>id</b></td>",
"<td><b>Gold</b></td>",
"<td><b>Model A</b></td>",
"<td><b>Model B</b></td>",
"</tr>",
'\n'.join(
'<tr>\n' +
'\n'.join('<td>{}</td>'.format(cell) for cell in row) +
'\n</tr>'
for row in table_content
),
'</table>'
))
def main():
with gr.Blocks(css=TABLE_CSS) as demo:
gr.Markdown(
"After uploading, click Run and switch to the Visualization tab."
)
with gr.Tabs():
with gr.TabItem("Upload"):
data = gr.File(
label='upload csv with Annotations', type='file'
)
run = gr.Button(label='Run')
with gr.TabItem("Visualization"):
viz = gr.HTML(label='Upload a csv file to start.')
run.click(colorize, data, viz)
demo.launch()
if __name__ == '__main__':
main()
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