| from transformers import pipeline |
| import streamlit as st |
| import requests |
| from bs4 import BeautifulSoup |
| import html |
| import time |
| from io import BytesIO |
| from reportlab.lib.pagesizes import A4 |
| from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle |
| from reportlab.platypus import SimpleDocTemplate, Paragraph |
| from reportlab.lib.enums import TA_JUSTIFY |
|
|
| |
| summarizer = pipeline("summarization", model="facebook/bart-large-cnn") |
|
|
| |
| st.set_page_config(layout="wide") |
|
|
|
|
| |
| def create_pdf(text): |
| pdf_buffer = BytesIO() |
| doc = SimpleDocTemplate(pdf_buffer, pagesize=A4) |
| styles = getSampleStyleSheet() |
| justified_style = ParagraphStyle( |
| name="JustifiedStyle", |
| parent=styles["BodyText"], |
| alignment=TA_JUSTIFY, |
| fontSize=12, |
| leading=15 |
| ) |
| paragraph = Paragraph(text, justified_style) |
| doc.build([paragraph]) |
| pdf_buffer.seek(0) |
| return pdf_buffer |
|
|
|
|
| |
| def main(): |
| st.title("Abstractive Article Summarizer") |
|
|
| url = st.text_input("Enter the URL of an article:", key="url") |
| max_chunk = 300 |
|
|
| if url: |
| try: |
| response = requests.get(url) |
| response.encoding = 'utf-8' |
| soup = BeautifulSoup(response.text, 'html.parser') |
| results = soup.find_all(['h1', 'p']) |
| text = [html.unescape(result.get_text()) for result in results] |
| article = ' '.join(text) |
|
|
| st.subheader("Extracted Article Content") |
| st.text_area("Article", article, height=300) |
| st.markdown(f"**Article Length:** {len(article)} characters") |
|
|
| article = article.replace('.', '.<eos>').replace('?', '?<eos>').replace('!', '!<eos>') |
| sentences = article.split('<eos>') |
| current_chunk = 0 |
| chunks = [[]] |
|
|
| for sentence in sentences: |
| if len(chunks[current_chunk]) + len(sentence.split(' ')) <= max_chunk: |
| chunks[current_chunk].extend(sentence.split(' ')) |
| else: |
| current_chunk += 1 |
| chunks.append(sentence.split(' ')) |
|
|
| for chunk_id in range(len(chunks)): |
| chunks[chunk_id] = ' '.join(chunks[chunk_id]) |
|
|
| progress_bar = st.progress(0) |
| status_text = st.empty() |
| summaries = [] |
| start_time = time.time() |
|
|
| for i, chunk in enumerate(chunks): |
| summary = summarizer(chunk, max_length=120, min_length=30, do_sample=False) |
| summaries.append(summary[0]['summary_text']) |
|
|
| percent_complete = (i + 1) / len(chunks) |
| elapsed_time = time.time() - start_time |
| estimated_total_time = elapsed_time / percent_complete |
| estimated_time_remaining = estimated_total_time - elapsed_time |
|
|
| progress_bar.progress(percent_complete) |
| status_text.markdown(f"**Progress:** {percent_complete * 100:.2f}% - " |
| f"**Estimated time remaining:** {estimated_time_remaining:.2f} seconds") |
|
|
| summary_text = ' '.join(summaries) |
|
|
| st.subheader("Summarized Article Content") |
| st.text_area("Summary", summary_text, height=300) |
| st.markdown(f"**Summary Length:** {len(summary_text)} characters") |
|
|
| pdf_buffer = create_pdf(summary_text) |
|
|
| |
| original_length = len(article.split()) |
| summary_length = len(summary_text.split()) |
| compression_ratio = (summary_length / original_length) * 100 |
|
|
| st.markdown(f"### Compression Ratio: {round(compression_ratio)}%") |
| if compression_ratio < 20: |
| st.success(f"Great Compression!\nThe summary is succinct and effectively highlights key points.") |
| elif 20 <= compression_ratio <= 40: |
| st.info(f"Well-balanced Summary.\nIt maintains essential details while being brief.") |
| else: |
| st.warning(f"Compression may be excessive.\nThe summary could be too brief and miss important details.") |
|
|
| |
| st.download_button( |
| label="Download Summary as PDF", |
| data=pdf_buffer, |
| file_name="summarized_article.pdf", |
| mime="application/pdf" |
| ) |
|
|
| except Exception as e: |
| st.warning(f"Error: {e}") |
|
|
|
|
| |
| if __name__ == '__main__': |
| main() |
|
|
