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| import gradio as gr | |
| from transformers import pipeline | |
| from bs4 import BeautifulSoup | |
| import requests | |
| from googlesearch import search | |
| import logging | |
| # Configure logging | |
| logging.basicConfig(level=logging.DEBUG) | |
| def summarize_news(query, num_results=3): | |
| logging.debug(f"Query received: {query}") | |
| logging.debug(f"Number of results requested: {num_results}") | |
| # Initialize summarization pipeline with a specific model | |
| logging.debug("Initializing summarization pipeline...") | |
| summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6") | |
| # Search for news articles | |
| logging.debug("Searching for news articles...") | |
| search_results = search(query, num_results=num_results) | |
| articles = [] | |
| logging.debug(f"Search results: {search_results}") | |
| for url in search_results: | |
| try: | |
| logging.debug(f"Fetching content from URL: {url}") | |
| # Fetch the content of the news article | |
| 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) | |
| # Chunk the article text | |
| logging.debug("Chunking the article text...") | |
| max_chunk = 500 | |
| 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: | |
| chunks.append(sentence.split(' ')) | |
| for chunk_id in range(len(chunks)): | |
| chunks[chunk_id] = ' '.join(chunks[chunk_id]) | |
| logging.debug(f"Chunks created: {chunks}") | |
| # Summarize the chunks | |
| logging.debug("Summarizing the chunks...") | |
| summaries = summarizer(chunks, max_length=120, min_length=30, do_sample=False) | |
| summary_text = " ".join([summary['summary_text'] for summary in summaries]) | |
| articles.append((url, summary_text)) | |
| logging.debug(f"Summary for URL {url}: {summary_text}") | |
| except Exception as e: | |
| logging.error(f"Error processing URL {url}: {e}") | |
| continue | |
| logging.debug(f"Final summarized articles: {articles}") | |
| return articles | |
| def format_output(articles): | |
| formatted_text = "" | |
| for url, summary in articles: | |
| formatted_text += f"URL: {url}\nSummary: {summary}\n\n" | |
| return formatted_text | |
| iface = gr.Interface( | |
| fn=lambda query, num_results: format_output(summarize_news(query, num_results)), | |
| inputs=[gr.inputs.Textbox(label="Query"), gr.inputs.Slider(minimum=1, maximum=10, default=3, label="Number of Results")], | |
| outputs="text", | |
| title="News Summarizer", | |
| description="Enter a query to get summarized versions of the top news articles." | |
| ) | |
| if __name__ == "__main__": | |
| logging.debug("Launching Gradio interface...") | |
| iface.launch() | |