Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| from news_service import NewsService | |
| import pandas as pd | |
| import html | |
| import time | |
| # Page Configuration | |
| st.set_page_config( | |
| page_title="NEXTER", | |
| page_icon="📰", | |
| layout="wide", | |
| initial_sidebar_state="expanded" | |
| ) | |
| # Custom CSS for better UI and to hide Deploy/Stop buttons | |
| st.markdown(""" | |
| <style> | |
| /* Hide Deploy button */ | |
| .stAppDeployButton { | |
| display: none !important; | |
| } | |
| /* Hide the 'Stop' button and the running status indicator to clean up UI */ | |
| [data-testid="stStatusWidget"] { | |
| display: none !important; | |
| } | |
| /* Hide the Main Menu (three dots/hamburger menu) */ | |
| #MainMenu { | |
| visibility: hidden !important; | |
| } | |
| /* Hide the footer (Made with Streamlit) */ | |
| footer { | |
| visibility: hidden !important; | |
| } | |
| /* Hide the header bar entirely */ | |
| /* header { | |
| visibility: hidden !important; | |
| } */ | |
| .main { | |
| background-color: #f0f2f6; | |
| } | |
| .stCard { | |
| background-color: white; | |
| padding: 1rem; | |
| border-radius: 12px; | |
| border: 1px solid #e0e0e0; | |
| margin-bottom: 1.5rem; | |
| box-shadow: 0 4px 6px rgba(0,0,0,0.05); | |
| transition: transform 0.2s ease-in-out; | |
| height: 480px; /* Fixed height for alignment */ | |
| display: flex; | |
| flex-direction: column; | |
| justify-content: space-between; | |
| } | |
| .stCard:hover { | |
| transform: translateY(-5px); | |
| box-shadow: 0 8px 15px rgba(0,0,0,0.1); | |
| } | |
| .card-img { | |
| width: 100%; | |
| height: 200px; /* Fixed image height */ | |
| object-fit: cover; | |
| border-radius: 8px; | |
| margin-bottom: 0.8rem; | |
| background-color: #f8f9fa; | |
| display: block; | |
| } | |
| .card-img-placeholder { | |
| width: 100%; | |
| height: 200px; | |
| background-color: #e9ecef; | |
| border-radius: 8px; | |
| margin-bottom: 0.8rem; | |
| display: flex; | |
| align-items: center; | |
| justify-content: center; | |
| color: #adb5bd; | |
| font-size: 0.9rem; | |
| } | |
| .card-title { | |
| font-size: 1.1rem; | |
| font-weight: 700; | |
| color: #1a1a1a; | |
| margin-bottom: 0.5rem; | |
| line-height: 1.4; | |
| height: 4.2rem; /* Fixed height for 3 lines of text */ | |
| display: -webkit-box; | |
| -webkit-line-clamp: 3; | |
| -webkit-box-orient: vertical; | |
| overflow: hidden; | |
| } | |
| .card-meta { | |
| font-size: 0.8rem; | |
| color: #6c757d; | |
| margin-bottom: 0.5rem; | |
| } | |
| .stArticle { | |
| background-color: white; | |
| padding: 2.5rem; | |
| border-radius: 15px; | |
| border: 1px solid #e9ecef; | |
| box-shadow: 0 10px 25px rgba(0,0,0,0.05); | |
| } | |
| .full-content { | |
| color: #212529; | |
| font-size: 1.1rem; | |
| line-height: 1.6; | |
| margin-top: 1rem; | |
| margin-bottom: 1rem; | |
| padding: 0; | |
| background-color: transparent; | |
| border-left: none; | |
| white-space: pre-wrap; | |
| } | |
| .summary-content { | |
| background-color: #e7f3ff; | |
| padding: 1.5rem; | |
| border-radius: 8px; | |
| border: 1px solid #b8daff; | |
| color: #004085; | |
| font-style: italic; | |
| } | |
| .meta-info { | |
| color: #6c757d; | |
| font-size: 0.9rem; | |
| margin-bottom: 1rem; | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| # --- CACHED FUNCTIONS --- | |
| def get_news_service(): | |
| return NewsService() | |
| def cached_fetch_all_news(_service, query, language="en"): | |
| return _service.fetch_all_news(query=query, language=language) | |
| def cached_get_full_content(_service, url): | |
| return _service.get_full_content(url) | |
| def cached_summarize_content(_service, text): | |
| return _service.summarize_content(text) | |
| def cached_split_into_sentences(_service, text): | |
| return _service.split_into_sentences(text) | |
| def cached_rate_bias(_service, text): | |
| return _service.rate_bias(text) | |
| def display_article_detail(article, news_service): | |
| """Displays the detailed view of a selected article with bias analysis and summary.""" | |
| if st.button("← Back to Feed"): | |
| st.session_state.selected_article = None | |
| st.rerun() | |
| url = article.get('link') | |
| if not url: | |
| st.error("Invalid article link.") | |
| return | |
| st.markdown('<div class="stArticle">', unsafe_allow_html=True) | |
| st.title(article.get('title', 'No Title')) | |
| # Hero image | |
| img_url = article.get('image_url') | |
| if img_url: | |
| st.image(img_url, use_container_width=True) | |
| st.markdown(f""" | |
| <div class="meta-info"> | |
| <b>Source:</b> {article.get('source_id', 'Unknown')} | | |
| <b>Date:</b> {article.get('pubDate', 'Unknown')} | | |
| <a href="{url}" target="_blank">Original Link</a> | |
| </div> | |
| """, unsafe_allow_html=True) | |
| with st.spinner("🧠 Analyzing article content..."): | |
| full_content = cached_get_full_content(news_service, url) | |
| # --- ROBUST FALLBACK LOGIC --- | |
| text_to_analyze = full_content | |
| status_msg = None | |
| # 1. Try Full Content | |
| if not text_to_analyze or len(text_to_analyze.strip()) < 100: | |
| # 2. Try Snippet/Description | |
| text_to_analyze = article.get('snippet') | |
| if text_to_analyze and len(text_to_analyze.strip()) > 20: | |
| status_msg = "⚠️ Full content extraction limited. Analyzing article snippet." | |
| else: | |
| # 3. Last Resort: Use Title | |
| text_to_analyze = article.get('title', '') | |
| status_msg = "⚠️ No content found. Analyzing article headline only." | |
| if not text_to_analyze: | |
| st.error("Could not retrieve any text for this article.") | |
| return | |
| if status_msg: | |
| st.warning(status_msg) | |
| # Display the text being analyzed | |
| with st.expander("📖 View Analyzed Text", expanded=True): | |
| st.markdown(f'<div style="font-size: 1rem; line-height: 1.5; color: #333;">{html.escape(text_to_analyze)}</div>', unsafe_allow_html=True) | |
| # AI Summary | |
| summary = cached_summarize_content(news_service, text_to_analyze) | |
| if summary: | |
| st.info(f"🤖 **AI Summary:** {summary}") | |
| st.divider() | |
| # Bias Analysis | |
| st.subheader("⚖️ Bias Analysis") | |
| overall_bias = cached_rate_bias(news_service, text_to_analyze) | |
| col_b1, col_b2 = st.columns([1, 3]) | |
| with col_b1: | |
| color = "#dc3545" if overall_bias['label'] == "Biased" else "#28a745" | |
| st.markdown(f"**Overall Rating:** <span style='color:{color}; font-weight:bold; font-size:1.2rem;'>{overall_bias['label']}</span>", unsafe_allow_html=True) | |
| with col_b2: | |
| st.progress(overall_bias['score'], text=f"Confidence: {overall_bias['score']:.1%}") | |
| # --- Interpretation Section --- | |
| if overall_bias['label'] == "Factual": | |
| st.success("✅ **Interpretation: Factual Content**\nThis article primarily uses objective language, reports verifiable events, and avoids subjective modifiers or emotional framing. It aims to inform rather than influence.") | |
| else: | |
| st.error("⚠️ **Interpretation: Biased Content**\nThis article contains elements that suggest a non-neutral perspective. This could include the use of loaded language, emotional appeals, or selective framing designed to influence the reader's opinion.") | |
| o_reasoning = overall_bias.get('reasoning', 'No specific reasoning provided.') | |
| st.warning(f"💡 **Analysis Reasoning:** {o_reasoning}") | |
| st.subheader("📋 Sentence-by-Sentence Breakdown") | |
| sentences = cached_split_into_sentences(news_service, text_to_analyze) | |
| sentence_html = "" | |
| for i, sentence in enumerate(sentences, 1): | |
| s_bias = cached_rate_bias(news_service, sentence) | |
| s_label = s_bias.get('label', 'Factual') | |
| s_reasoning = s_bias.get('reasoning', '') | |
| s_color = "rgba(220, 53, 69, 0.08)" if s_label == "Biased" else "transparent" | |
| escaped_sentence = html.escape(sentence) | |
| escaped_reasoning = html.escape(s_reasoning) | |
| reasoning_html = f'<div style="font-size: 0.85rem; color: #721c24; margin-top: 4px; font-style: italic;">Why? {escaped_reasoning}</div>' if s_label == "Biased" else "" | |
| border_style = "border-left: 4px solid #dc3545;" if s_label == "Biased" else "border-left: 4px solid #e9ecef;" | |
| sentence_html += f'<div style="margin-bottom: 12px; padding: 12px; background-color: {s_color}; border-radius: 6px; {border_style}"><b>{i}.</b> {escaped_sentence} <span style="font-size: 0.8rem; color: #6c757d; margin-left: 10px; font-weight: bold;">[{s_label}]</span>{reasoning_html}</div>' | |
| st.markdown(f'<div class="full-content" style="border:none; padding:0;">{sentence_html}</div>', unsafe_allow_html=True) | |
| st.markdown('</div>', unsafe_allow_html=True) | |
| def fetch_and_display_news(query, news_service, title=None): | |
| """Fetches and displays news in a grid layout.""" | |
| if title: | |
| st.subheader(title) | |
| spinner_text = f"🔍 Searching for '{query}'..." if query else "🔍 Fetching latest headlines..." | |
| with st.spinner(spinner_text): | |
| try: | |
| articles = cached_fetch_all_news(news_service, query, language="en") | |
| if not articles: | |
| st.error("No articles found for this topic. Please try another one.") | |
| return | |
| # Grid layout: 3 columns | |
| articles = articles[:12] | |
| cols = st.columns(3) | |
| for idx, article in enumerate(articles): | |
| with cols[idx % 3]: | |
| st.markdown('<div class="stCard">', unsafe_allow_html=True) | |
| # Thumbnail Image handling | |
| img_url = article.get('image_url') | |
| if img_url and img_url.startswith('http'): | |
| st.markdown(f'<img src="{img_url}" class="card-img" onerror="this.style.display=\'none\'; this.nextSibling.style.display=\'flex\';">', unsafe_allow_html=True) | |
| st.markdown('<div class="card-img-placeholder" style="display:none;">🖼️ Image Unavailable</div>', unsafe_allow_html=True) | |
| else: | |
| st.markdown('<div class="card-img-placeholder">🖼️ No Image</div>', unsafe_allow_html=True) | |
| # Source and Date | |
| date_str = article.get('pubDate', 'Unknown')[:10] | |
| st.markdown(f'<div class="card-meta">{article.get("source_id", "Unknown")} • {date_str}</div>', unsafe_allow_html=True) | |
| # Title | |
| st.markdown(f'<div class="card-title">{article.get("title", "No Title")}</div>', unsafe_allow_html=True) | |
| # Analyze Button | |
| if st.button("Analyze Article", key=f"btn_{idx}", use_container_width=True): | |
| st.session_state.selected_article = article | |
| st.rerun() | |
| st.markdown('</div>', unsafe_allow_html=True) | |
| except Exception as e: | |
| st.error(f"Error fetching news: {str(e)}") | |
| def main(): | |
| st.title("📰 NEXTER") | |
| st.markdown("Modern AI-Powered News Analysis") | |
| # Initialize session states | |
| if 'search_query' not in st.session_state: st.session_state.search_query = "" | |
| if 'selected_article' not in st.session_state: st.session_state.selected_article = None | |
| if 'is_home' not in st.session_state: st.session_state.is_home = True | |
| with st.sidebar: | |
| st.header("Search Settings") | |
| news_service = get_news_service() | |
| query_input = st.text_input("Topic Search", value=st.session_state.search_query, placeholder="e.g. Finance, AI, Sports") | |
| if query_input != st.session_state.search_query: | |
| st.session_state.search_query = query_input | |
| st.session_state.selected_article = None | |
| st.session_state.is_home = False | |
| if st.button("Fetch News", type="primary"): | |
| st.session_state.selected_article = None | |
| st.session_state.is_home = False | |
| st.rerun() | |
| if st.button("🏠 Home Feed"): | |
| st.session_state.search_query = "" | |
| st.session_state.selected_article = None | |
| st.session_state.is_home = True | |
| st.rerun() | |
| st.divider() | |
| if st.button("🧹 Clear Cache"): | |
| st.cache_data.clear() | |
| st.success("Cache cleared!") | |
| time.sleep(0.5) | |
| st.rerun() | |
| if news_service.bias_model: | |
| st.success("✅ AI Bias Model Loaded") | |
| else: | |
| st.info("☁️ Cloud Analysis Active") | |
| # Display logic | |
| if st.session_state.selected_article: | |
| display_article_detail(st.session_state.selected_article, news_service) | |
| elif st.session_state.is_home: | |
| fetch_and_display_news(None, news_service, title="Top Headlines") | |
| else: | |
| fetch_and_display_news(st.session_state.search_query, news_service, title=f"Results for: {st.session_state.search_query}") | |
| if __name__ == "__main__": | |
| main() | |