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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 | |
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) | |
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) | |
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) |