JoBeer commited on
Commit
1e717cf
·
1 Parent(s): bb29b0a

Update app.py

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Files changed (1) hide show
  1. app.py +17 -2
app.py CHANGED
@@ -27,14 +27,29 @@ def predict(name, description):
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  IRDI2 = corpus.iloc[output[0][1].get('corpus_id'),4]
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  score2 = output[0][1].get('score')
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- df = [[preferedName1, definition1, IRDI1, score1], [preferedName2, definition2, IRDI1, score2]]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  return pd.DataFrame(df)
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  interface = gr.Interface(fn = predict,
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  inputs = [gr.Textbox(label="Name:", placeholder="z.B. GTIN", lines=1), gr.Textbox(label="Description:", placeholder="z.B. Globel Trade Item Number", lines=1)],
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  #outputs = [gr.Textbox(label = 'preferedName'),gr.Textbox(label = 'definition'), gr.Textbox(label = 'IDRI'),gr.Textbox(label = 'score')],
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- outputs = [gr.Dataframe(row_count = (2, "fixed"), col_count=(4, "fixed"), label="Predictions", headers=['preferedName', 'definition', 'IRDI', 'score'])],
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  examples = [['GTIN', 'Globel Trade Item Number'], ['Global Trade Item Number', 'the identification number from the GS1 system with which the trading units can be uniquely identified worldwide'],
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  ['Device type', 'describing a set of common specific characteristics in products or goods'], ['Item type','the type of product, an item can be assigned to'],
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  ['Nominal power','power being consumed by or dissipated within an electric component as a variable'], ['Power consumption', 'power that is typically taken from the auxiliary power supply when the device is operating normally']], theme = 'huggingface',
 
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  IRDI2 = corpus.iloc[output[0][1].get('corpus_id'),4]
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  score2 = output[0][1].get('score')
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+ preferedName3 = corpus.iloc[output[0][2].get('corpus_id'),2]
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+ definition3 = corpus.iloc[output[0][2].get('corpus_id'),1]
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+ IRDI3 = corpus.iloc[output[0][2].get('corpus_id'),4]
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+ score3 = output[0][2].get('score')
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+
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+ preferedName4 = corpus.iloc[output[0][3].get('corpus_id'),2]
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+ definition4 = corpus.iloc[output[0][3].get('corpus_id'),1]
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+ IRDI4 = corpus.iloc[output[0][3].get('corpus_id'),4]
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+ score4 = output[0][3].get('score')
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+
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+ preferedName5 = corpus.iloc[output[0][4].get('corpus_id'),2]
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+ definition5 = corpus.iloc[output[0][4].get('corpus_id'),1]
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+ IRDI5 = corpus.iloc[output[0][4].get('corpus_id'),4]
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+ score5 = output[0][4].get('score')
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+
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+ df = [[preferedName1, IRDI1, score1], [preferedName2, IRDI2, score2],[preferedName3, IRDI3, score3],[preferedName4, IRDI4, score4], [preferedName5, IRDI5, score5]]
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  return pd.DataFrame(df)
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  interface = gr.Interface(fn = predict,
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  inputs = [gr.Textbox(label="Name:", placeholder="z.B. GTIN", lines=1), gr.Textbox(label="Description:", placeholder="z.B. Globel Trade Item Number", lines=1)],
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  #outputs = [gr.Textbox(label = 'preferedName'),gr.Textbox(label = 'definition'), gr.Textbox(label = 'IDRI'),gr.Textbox(label = 'score')],
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+ outputs = [gr.Dataframe(row_count = (5, "fixed"), col_count=(3, "fixed"), label="Predictions", headers=['preferedName', 'IRDI', 'score'])],
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  examples = [['GTIN', 'Globel Trade Item Number'], ['Global Trade Item Number', 'the identification number from the GS1 system with which the trading units can be uniquely identified worldwide'],
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  ['Device type', 'describing a set of common specific characteristics in products or goods'], ['Item type','the type of product, an item can be assigned to'],
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  ['Nominal power','power being consumed by or dissipated within an electric component as a variable'], ['Power consumption', 'power that is typically taken from the auxiliary power supply when the device is operating normally']], theme = 'huggingface',