Commit ·
db40a0b
1
Parent(s): aebc3f2
Create app.py
Browse files
app.py
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from __future__ import absolute_import, division, print_function, unicode_literals
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import os
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import gc
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import gradio as gr
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import pandas as pd
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from transformers import pipeline
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def huggingface_result_page(paragraph):
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if article.strip():
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model_base = pipeline('sentiment-analysis')
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sen_list = paragraph
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sen_list = sen_list.split('\n')
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sen_list_temp = sen_list[0:]
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results = []
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temp_result_dict = []
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for sen in sen_list_temp:
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sen = sen.strip()
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if sen:
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cur_result = model_base(sen)[0]
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temp_result_dict.append(sen)
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results.append(cur_result['label'])
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result = {
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'Input': sen_list, 'Sentiment': results
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}
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print("LENGTH of results ====> ",str(len(results)))
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print("LENGTH of sen_list ====> ",str(len(temp_result_dict)))
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return pd.DataFrame(result)
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else:
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raise gr.Error("Please enter text in inputbox!!!!")
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inputs = gr.Textbox(lines=10, label="Paragraph")
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outputs = gr.Dataframe(row_count = (3, "dynamic"), col_count=(2, "fixed"), label="Here is the Result", headers=["Input","Sentiment"],wrap=True)
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demo = gr.Interface(
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huggingface_result_page,
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inputs,
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outputs,
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title="Huggingface Sentiment Analysis",
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css=".gradio-container {background-color: lightgray}",
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article = """Provide us your feedback on this demo and feel free to contact us at <a href="mailto:letstalk@pragnakalp.com" target="_blank">letstalk@pragnakalp.com</a>
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if you want to have your own sentiment analysis system. We will be happy to serve you for your sentiment analysis requirement.
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And don't forget to check out more interesting <a href="https://www.pragnakalp.com/services/natural-language-processing-services/" target="_blank">NLP services</a>
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we are offering.
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<p style='text-align: center;'>Developed by :<a href="https://www.pragnakalp.com" target="_blank"> Pragnakalp Techlabs</a></p>"""
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)
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demo.launch()
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