Prathap commited on
Commit
433d73e
·
1 Parent(s): 1ab6c4b

Update app.py

Browse files

added about section

Files changed (1) hide show
  1. app.py +33 -9
app.py CHANGED
@@ -1,15 +1,19 @@
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- #author:prathap
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-
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  from transformers import pipeline
 
 
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  from bs4 import BeautifulSoup
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- import torch
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  import requests
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- import pandas as pd
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  import streamlit as st
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  import warnings
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  warnings.filterwarnings("ignore")
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- st.title("Automatic summarization")
 
 
 
 
 
 
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  @st.cache(allow_output_mutation=True)
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  def pipen():
@@ -17,10 +21,17 @@ def pipen():
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  return summarizer
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- url = st.text_input('The URL link')
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  if st.button("Submit"):
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  r = requests.get(url)
@@ -33,6 +44,7 @@ if st.button("Submit"):
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  ARTICLE = ARTICLE.replace('?', '?<eos>')
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  ARTICLE = ARTICLE.replace('!', '!<eos>')
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  sentences = ARTICLE.split('<eos>')
@@ -56,9 +68,21 @@ if st.button("Submit"):
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  model=pipen()
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  res = model(chunks, max_length=120, min_length=30, do_sample=False)
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  text = ' '.join([summ['summary_text'] for summ in res])
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- print(len(text))
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  st.write("Success")
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  st.write(text)
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- with open('stsummary.txt', 'w') as f:
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- f.write(text)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  from transformers import pipeline
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+ import base64
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+ import time
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  from bs4 import BeautifulSoup
 
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  import requests
 
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  import streamlit as st
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  import warnings
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  warnings.filterwarnings("ignore")
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+
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+
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+ timestr = time.strftime("%Y%m%d-%H%M%S")
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+
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+ st.markdown(' Created by **_Prathap_**. :baby_chick:')
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+
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+ st.title("Automatic text summarization")
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  @st.cache(allow_output_mutation=True)
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  def pipen():
 
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  return summarizer
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+ def text_downloader(raw_text):
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+ b64 = base64.b64encode(raw_text.encode()).decode()
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+ new_filename = "new_text_file_{}_.txt".format(timestr)
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+ st.markdown("#### Download File ###")
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+ href = f'<a href="data:file/txt;base64,{b64}" download="{new_filename}">Click Here!!</a>'
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+ st.markdown(href,unsafe_allow_html=True)
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+
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+ url = st.text_input('Paste URL ⤵️')
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  if st.button("Submit"):
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  r = requests.get(url)
 
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  ARTICLE = ARTICLE.replace('?', '?<eos>')
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  ARTICLE = ARTICLE.replace('!', '!<eos>')
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+
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  sentences = ARTICLE.split('<eos>')
 
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  model=pipen()
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  res = model(chunks, max_length=120, min_length=30, do_sample=False)
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  text = ' '.join([summ['summary_text'] for summ in res])
 
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  st.write("Success")
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  st.write(text)
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+ text_downloader(text)
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+
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+
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+ if st.button("Contact"):
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+ st.write("Hi there, I'm Prathap 👋. 2+ years Applied Deep Learning experience")
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+ st.write("✅ [LinkedIn](www.linkedin.com/in/prathapreddyk)")
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+ st.write(" 📚[Github](https://github.com/Pratap517)")
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+ st.write(" 📗Analyze Csv files in one step [Click Here](https://share.streamlit.io/pratap517/streamlitapp_dataanalysis/main/main_app.py)")
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+ st.write(" 😷 Face Mask Detection App [Click Here](https://mask-detection-5a800.firebaseapp.com/)")
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