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| import streamlit as st | |
| import requests | |
| import os | |
| from newspaper import Article | |
| from PIL import Image | |
| from io import BytesIO | |
| from deep_translator import GoogleTranslator | |
| from langdetect import detect | |
| from transformers import pipeline | |
| # Function to detect language | |
| def detect_language(text): | |
| try: | |
| # Detect the language | |
| lang = detect(text) | |
| return lang | |
| except Exception as e: | |
| print("Error detecting language:", str(e)) | |
| return None | |
| # Function to translate text to English | |
| def translate_text(text): | |
| try: | |
| # Detect the source language | |
| source_language = detect(text) | |
| if source_language is None: | |
| return None, "Language detection failed." | |
| # Translate the text to English | |
| translated_text = GoogleTranslator(source=source_language, target='en').translate(text) | |
| return translated_text, source_language | |
| except Exception as e: | |
| return None, str(e) | |
| # Function to fetch article content from URL | |
| def fetch_article(url): | |
| article = Article(url) | |
| article.download() | |
| article.parse() | |
| return article.text, article.top_image if hasattr(article, 'top_image') else None | |
| # Function to query Hugging Face API for summarization | |
| def query(payload): | |
| API_URL = "https://api-inference.huggingface.co/models/facebook/bart-large-cnn" | |
| api_key = os.environ.get("HUGGING_FACE_API_KEY") | |
| headers = {"Authorization": f"Bearer {api_key}"} | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| return response.json() | |
| # Main function | |
| def main(): | |
| # Enable session state to store translated text | |
| session_state = st.session_state | |
| if not hasattr(session_state, 'translated_text'): | |
| session_state.translated_text = "" | |
| st.set_page_config( | |
| page_title="Multifunctional News App", | |
| page_icon="🌐", | |
| layout="wide" | |
| ) | |
| st.title("MultiLingua NewsHub 🌐📰") | |
| st.markdown("Breaking Language Barriers: Explore Global News, Summarized in English.") | |
| # Sidebar configuration | |
| st.sidebar.subheader("User Input Options") | |
| input_option = st.sidebar.radio("", ["URL", "Text"]) | |
| if input_option == "URL": | |
| # Collect user input (URL) | |
| url = st.sidebar.text_input("Enter the URL of the news article:") | |
| data, image_url = fetch_article(url) if url else ("", None) | |
| else: | |
| # Collect user input (Direct Text) | |
| data = st.sidebar.text_area("Enter the text for translation and summarization in any language:", height=300) | |
| image_url = None | |
| # Translate when the user clicks the button | |
| if st.sidebar.button("Translate to En"): | |
| translated_text, detected_language = translate_text(data) | |
| st.markdown("---") | |
| # Display detected language message | |
| if detected_language: | |
| st.info(f"Language detected: {detected_language}") | |
| st.subheader(f"Original Text ({detected_language}):") | |
| st.text_area("", value=data, height=300) | |
| st.markdown("---") | |
| st.subheader("Translated Text (English):") | |
| st.text_area("", value=translated_text, height=300) | |
| # Use the translated text for summarization | |
| session_state.translated_text = translated_text | |
| st.sidebar.subheader("Summarization Settings") | |
| max_length = st.sidebar.slider("Select the maximum length for the summary:", min_value=20, max_value=500, value=150) | |
| show_original_text = st.sidebar.checkbox("Show Original Text", value=True) | |
| # Summarize when the user clicks the button | |
| if st.sidebar.button("Summarize"): | |
| # Check if translated text is available | |
| if not session_state.translated_text: | |
| st.warning("Please translate the text first.") | |
| else: | |
| min_length = max_length // 4 | |
| payload = { | |
| "inputs": session_state.translated_text, | |
| "parameters": {"min_length": min_length, "max_length": max_length}, | |
| } | |
| # Query the Hugging Face API | |
| output = query(payload) | |
| # Display the original text and summary side by side | |
| col1, col2 = st.columns(2) | |
| if show_original_text: | |
| with col1: | |
| st.subheader("Original Text:") | |
| st.text_area(" ", value=data, height=500) | |
| with col2: | |
| st.subheader("Summary:") | |
| if isinstance(output, list) and output and "summary_text" in output[0]: | |
| st.write(output[0]["summary_text"]) | |
| elif isinstance(output, dict) and "summary_text" in output: | |
| st.write(output["summary_text"]) | |
| else: | |
| st.warning("Summary not available. Please check the input and try again.") | |
| # Add 2 lines space | |
| st.text("\n\n") | |
| # Display the image under the summary | |
| if image_url: | |
| st.image(image_url, caption="Image from the article", use_column_width=True) | |
| else: | |
| # If original text is not shown, make summary and image larger | |
| st.subheader("Summary:") | |
| if isinstance(output, list) and output and "summary_text" in output[0]: | |
| st.write(output[0]["summary_text"]) | |
| elif isinstance(output, dict) and "summary_text" in output: | |
| st.write(output["summary_text"]) | |
| else: | |
| st.warning("Summary not available. Please check the input and try again.") | |
| # Add 2 lines space | |
| st.text("\n\n\n") | |
| # Display the image under the summary | |
| if image_url: | |
| st.image(image_url, caption="Image from the article", use_column_width=True) | |
| # Add GitHub link in the side panel | |
| st.markdown( | |
| '<div style="position: fixed; bottom: 10px; right: 10px;">' | |
| '<a href="https://github.com/sg-sparsh-goyal" target="_blank">' | |
| '<img src="https://img.shields.io/badge/GitHub-Profile-blue?style=social&logo=github" alt="GitHub">' | |
| '</a>' | |
| '</div>', | |
| unsafe_allow_html=True | |
| ) | |
| if __name__ == "__main__": | |
| main() | |