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import gradio as gr
import requests
from newspaper import Article
from transformers import pipeline
import nltk
import os
import PyPDF2
# Load summarization pipeline
summarizer = pipeline("summarization", model="harao-ml/flant5-finetuned-summarize")
# Function to split text into smaller chunks
def split_text(text, max_tokens=512):
words = text.split()
for i in range(0, len(words), max_tokens):
yield ' '.join(words[i:i + max_tokens])
# Function to clean text
def clean_text(text):
text = ' '.join(text.split())
text = ' '.join(word for word in text.split() if len(word) < 100)
return text
# Helper function to fetch and parse an article from a URL
def fetch_article_details(url):
try:
article = Article(url)
article.download()
article.parse()
title = article.title or "Untitled"
author = ", ".join(article.authors) if article.authors else "Unknown"
pub_date = article.publish_date.strftime('%B %d, %Y') if article.publish_date else "Unknown"
return title, author, pub_date, article.text
except Exception as e:
return None, None, None, f"Error fetching article: {str(e)}"
# Helper function to generate a summary
def generate_summary(content):
if not content.strip():
return "No input provided."
text = content
cleaned_text = clean_text(text)
chunks = list(split_text(cleaned_text))
cons_summary = ''.join([summarizer(chunk, do_sample=False)[0]['summary_text'] for chunk in chunks if chunk.strip()]) if chunks else ''
summary = summarizer(text, do_sample=False)[0]['summary_text']
return summary
# Summarize from text or URL
def summarize_input(mixed_input):
if mixed_input.startswith("http://") or mixed_input.startswith("https://"):
title, author, pub_date, content = fetch_article_details(mixed_input)
if content.startswith("Error"):
return f"### Error\n\n{content}"
summary = generate_summary(content)
return f"**Title:** {title}\n\n**Author(s):** {author}\n\n**Published:** {pub_date}\n\n**π Summary** \n\n{summary}\n\n[π Read more]({mixed_input})\n\n---"
else:
summary = generate_summary(mixed_input)
return f"## π Summary \n\n{summary}\n\nπ **Original Text:**\n\n{mixed_input}\n\n---"
# Function to summarize a file (PDF or TXT)
def summarize_file(file):
try:
if file is None: # Handle the case where no file is provided
return "" # Return an empty string instead of an error message
text = ""
if file.name.endswith(".pdf"):
with open(file.name, "rb") as f:
reader = PyPDF2.PdfReader(f)
for page in reader.pages:
text += page.extract_text() or ""
elif file.name.endswith(".txt"):
with open(file.name, "r", encoding="utf-8") as f:
text = f.read()
else:
return "β Unsupported file type."
if not text.strip():
return "β No text found in file."
summary = generate_summary(text)
original_text = text
# Combine the outputs into a single string
result = (
f"### π Summary\n\n"
f"{summary}\n\n"
f"---\n\n"
f"π **Original Extracted Text:**\n\n{original_text}"
)
return result
except Exception as e:
return f"β Error processing file: {str(e)}"
# Function to fetch top headlines from NewsAPI and summarize them
def fetch_news():
url = 'https://newsapi.org/v2/top-headlines'
api_key = os.environ.get("api_key")
params = {
'apiKey': api_key,
'language': 'en',
'sources': 'associated-press',
'pageSize': 10
}
try:
response = requests.get(url, params=params)
if response.status_code != 200:
return f"Error: Failed to fetch news. Status code: {response.status_code}"
articles = response.json().get("articles", [])
summaries = [f'## π° Top Stories - Instant Insights\n\n']
for article in articles:
title = article.get("title", "No title")
article_url = article.get("url", "#")
author = article.get("author", "Unknown")
pub_date = article.get("publishedAt", "Unknown")
content = extract_full_content(article_url) or article.get("content") or article.get("description") or ""
summary = generate_summary(content)
summaries.append(f"**{title}** \n\n**Author(s):** {author}\n\n**Published:** {pub_date}\n\n**π Summary:** {summary}\n\n [π Read more]({article_url})\n\n---")
if not summaries:
return "### No articles could be summarized."
return "\n\n".join(summaries)
except Exception as e:
return f"### Error fetching news\n\n{str(e)}"
# Helper function to extract full content using newspaper3k
def extract_full_content(url):
try:
article = Article(url)
article.download()
article.parse()
return article.text
except Exception:
return None
# Gradio interface
with gr.Blocks(theme=gr.themes.Default(font="Arial", font_mono="Courier New")) as demo:
# Header Section
gr.Markdown("# π° Sum Up! Stay Informed, Instantly")
gr.Markdown("### FLAN-T5-Driven Summarizer for Multi-Format Content")
gr.Markdown("Sum Up! effectively distills lengthy content into clear, concise summaries with just a text input, file upload, or URL. Stay informed with instant access to auto-summarized top news headlinesβall in just one click.")
# Input Section
gr.Markdown("---") # Horizontal line for separation
with gr.Row():
# Left Column: Collapsible Sidebar for Latest News
with gr.Column(scale=1, min_width=300):
with gr.Accordion("π’ News at a Glance", open=False):
gr.Markdown("**Source: Associated Press**")
gr.Markdown(
"Click to get today's top news from the Associated Press, simplified and ready to read.")
news_btn = gr.Button("β‘ News Now", variant="primary", elem_id="news-now-btn")
# Right Column: Text Input and File Upload
with gr.Column(scale=2, min_width=400):
gr.Markdown("### Provide content to summarize")
gr.Markdown("#### Enter Text or URL")
input_box = gr.Textbox(
label="Enter URL or Text",
placeholder="Paste a URL or text here...",
lines=5,
)
summarize_btn = gr.Button("π Summarize", variant="primary", elem_id="summarize-btn")
# Clear Button placed below the Summarize button
clear_btn = gr.Button("Clear", variant="secondary", elem_id="clear-btn")
gr.Markdown("#### Upload a File")
file_input = gr.File(
label="Upload a .pdf or .txt file", file_types=[".pdf", ".txt"]
)
gr.Markdown("**Note:** Only PDF and TXT files are supported.")
# Output Section
gr.Markdown("---") # Horizontal line for separation
gr.Markdown("### π‘ Key Takeaways")
with gr.Row():
with gr.Column(scale=1):
gen_output = gr.Markdown() # Use a valid output component
# Link buttons to their respective functions
summarize_btn.click(fn=summarize_input, inputs=input_box, outputs=gen_output)
file_input.change(fn=summarize_file, inputs=file_input, outputs=gen_output)
news_btn.click(fn=fetch_news, inputs=[], outputs=gen_output)
# Clear button functionality
clear_btn.click(
fn=lambda: ("", None, ""), # Clear all inputs and outputs
inputs=[],
outputs=[input_box, file_input, gen_output],
)
# Ensure gen_output is properly reset
gen_output = gr.Markdown(value="") # Initialize with an empty value
# Add custom CSS for better styling
css = """
#summarize-btn {
background-color: #4CAF50 !important; /* Green for Summarize */
color: white !important;
font-size: 16px !important;
padding: 10px 20px !important;
border-radius: 5px !important;
margin-top: 20px !important;
width: 100%;
}
#news-now-btn {
background-color: #0078D7 !important; /* Blue for News Now */
color: white !important;
font-size: 16px !important;
padding: 10px 20px !important;
border-radius: 5px !important;
margin-top: 20px !important;
width: 100%;
}
#clear-btn {
background-color: #d6d8db !important; /* Lighter Gray for Clear */
color: black !important;
font-size: 16px !important;
padding: 10px 20px !important;
border-radius: 5px !important;
margin-top: 20px !important;
width: 100%;
}
"""
# Apply the custom CSS
demo.css = css
if __name__ == "__main__":
demo.launch() |