import os import threading from flask import Flask, render_template, request, jsonify from rss_processor import fetch_rss_feeds, process_and_store_articles, vector_db import logging app = Flask(__name__) # Setup logging logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) # Global flag to track background loading loading_complete = False def load_feeds_in_background(): global loading_complete try: logger.info("Starting background RSS feed fetch") articles = fetch_rss_feeds() logger.info(f"Fetched {len(articles)} articles") process_and_store_articles(articles) logger.info("Background feed processing complete") loading_complete = True except Exception as e: logger.error(f"Error in background feed loading: {e}") loading_complete = True # Mark as complete even on error to avoid infinite polling @app.route('/') def index(): global loading_complete loading_complete = False # Reset on each load # Start background feed loading threading.Thread(target=load_feeds_in_background, daemon=True).start() try: # Retrieve the 10 most recent articles from Chroma DB all_docs = vector_db.get(include=['documents', 'metadatas']) if not all_docs.get('metadatas'): logger.info("No articles in DB yet") return render_template("index.html", categorized_articles={}, has_articles=False, loading=True) # Sort by 'published' date (if available) and take top 10 enriched_articles = [] seen_keys = set() for doc, meta in zip(all_docs['documents'], all_docs['metadatas']): if not meta: continue title = meta.get("title", "No Title") link = meta.get("link", "") key = f"{title}|{link}" if key not in seen_keys: seen_keys.add(key) enriched_articles.append({ "title": title, "link": link, "description": meta.get("original_description", "No Description"), "category": meta.get("category", "Uncategorized"), "published": meta.get("published", "Unknown Date"), "image": meta.get("image", "svg"), }) # Sort by published date (assuming it's in a parseable format; fallback to order if not) enriched_articles.sort(key=lambda x: x["published"], reverse=True) recent_articles = enriched_articles[:10] logger.info(f"Displaying {len(recent_articles)} recent articles") # Categorize recent articles categorized_articles = {} for article in recent_articles: cat = article["category"] categorized_articles.setdefault(cat, []).append(article) return render_template("index.html", categorized_articles=categorized_articles, has_articles=True, loading=True) except Exception as e: logger.error(f"Error retrieving recent articles: {e}") return render_template("index.html", categorized_articles={}, has_articles=False, loading=True) @app.route('/search', methods=['POST']) def search(): query = request.form.get('search') if not query: return render_template("index.html", categorized_articles={}, has_articles=False, loading=False) try: logger.info(f"Searching for: {query}") results = vector_db.similarity_search(query, k=10) enriched_articles = [] seen_keys = set() for doc in results: meta = doc.metadata title = meta.get("title", "No Title") link = meta.get("link", "") key = f"{title}|{link}" if key not in seen_keys: seen_keys.add(key) enriched_articles.append({ "title": title, "link": link, "description": meta.get("original_description", "No Description"), "category": meta.get("category", "Uncategorized"), "published": meta.get("published", "Unknown Date"), "image": meta.get("image", "svg"), }) categorized_articles = {} for article in enriched_articles: cat = article["category"] categorized_articles.setdefault(cat, []).append(article) return render_template("index.html", categorized_articles=categorized_articles, has_articles=bool(enriched_articles), loading=False) except Exception as e: logger.error(f"Search error: {e}") return render_template("index.html", categorized_articles={}, has_articles=False, loading=False) @app.route('/check_loading', methods=['GET']) def check_loading(): global loading_complete if loading_complete: return jsonify({"status": "complete"}) return jsonify({"status": "loading"}), 202 if __name__ == "__main__": app.run(host="0.0.0.0", port=7860)