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Upload app.py
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app.py
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import streamlit
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import pandas as pd
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import torch
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from transformers import pipeline
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import streamlit as st
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def app():
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st.title("Text Summarization 🤓")
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st.markdown("This is a Web application that Summarizes Text 😎")
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upload_file = st.file_uploader('Upload a file containing Text data')
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button = st.button("Summarize")
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st.cache(allow_output_mutation=True)
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def facebook_bart_model():
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summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
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return summarizer
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summarizer= facebook_bart_model()
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def text_summarizer(text):
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a = summarizer(text, max_length=150, min_length=30, do_sample=False)
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return a[0]['summary_text']
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# Check to see if a file has been uploaded
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if upload_file is not None and button:
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st.success("Summarizing Text, Please wait...")
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# If it has then do the following:
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# Read the file to a dataframe using pandas
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df = pd.read_csv(upload_file)
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# Create a section for the dataframe header
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df1 = df.copy()
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df1['summarized_text'] = df1['Dialog'].apply(text_summarizer)
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df2 = df1[['Name','summarized_text']]
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st.write(df2.head(5))
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@st.cache
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def convert_df(dataframe):
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return dataframe.to_csv().encode('utf-8')
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csv = convert_df(df2)
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st.download_button(label="Download CSV", data=csv, file_name='summarized_output.csv', mime='text/csv')
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if __name__ == "__main__":
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app()
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