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