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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") | |
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/)") | |