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from transformers import pipeline
import base64
import time
from bs4 import BeautifulSoup
import requests
import streamlit as st
import warnings
warnings.filterwarnings("ignore")
timestr = time.strftime("%Y%m%d-%H%M%S")
st.markdown(' Created by **_Prathap_**. :baby_chick:')
st.title("Automatic text summarization")
@st.cache(allow_output_mutation=True)
def pipen():
summarizer = pipeline("summarization")
return summarizer
def text_downloader(raw_text):
b64 = base64.b64encode(raw_text.encode()).decode()
new_filename = "new_text_file_{}_.txt".format(timestr)
st.markdown("#### Download File ###")
href = f'<a href="data:file/txt;base64,{b64}" download="{new_filename}">Click Here!!</a>'
st.markdown(href,unsafe_allow_html=True)
url = st.text_input('Paste URL ⤵️')
if st.button("Submit"):
r = requests.get(url)
soup = BeautifulSoup(r.text, 'html.parser')
results = soup.find_all(['h1', 'p'])
text = [result.text for result in results]
ARTICLE = ' '.join(text)
max_chunk = 400
ARTICLE = ARTICLE.replace('.', '.<eos>')
ARTICLE = ARTICLE.replace('?', '?<eos>')
ARTICLE = ARTICLE.replace('!', '!<eos>')
sentences = ARTICLE.split('<eos>')
current_chunk = 0
chunks = []
for sentence in sentences:
if len(chunks) == current_chunk + 1:
if len(chunks[current_chunk]) + len(sentence.split(' '))<= max_chunk:
chunks[current_chunk].extend(sentence.split(' '))
else:
current_chunk += 1
chunks.append(sentence.split(' '))
else:
print(current_chunk)
chunks.append(sentence.split(' '))
for chunk_id in range(len(chunks)):
chunks[chunk_id] = ' '.join(chunks[chunk_id])
with st.spinner("Loading the Model into the memory...."):
model=pipen()
res = model(chunks, max_length=50, min_length=30, do_sample=False)
text = ' '.join([summ['summary_text'] for summ in res])
st.write("Success")
st.write(text)
text_downloader(text)
if st.button("Contact"):
st.write("Hi there, I'm Prathap 👋. 2+ years Applied Deep Learning experience")
st.write("✅ [LinkedIn](https://linkedin.com/in/prathapreddyk)")
st.write(" 📚[Github](https://github.com/Pratap517)")
st.write(" 📗Analyze Csv files in one step [Click Here](https://data-analyse-prathap.herokuapp.com)")
st.write(" 😷 Face Mask Detection App [Click Here](https://mask-detection-5a800.firebaseapp.com/)")
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