108 lines
3.2 KiB
Python
108 lines
3.2 KiB
Python
# main.py
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import json
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import os
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from datetime import datetime
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import feedparser
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from utils.image_extractor import extract_images_with_metadata
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from openai import OpenAI
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from dotenv import load_dotenv
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import logging
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load_dotenv()
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# Log-Verzeichnis sicherstellen
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os.makedirs("logs", exist_ok=True)
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client = OpenAI()
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# 📝 Logging konfigurieren
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logging.basicConfig(filename='logs/rss_tool.log', level=logging.INFO)
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ARTICLES_FILE = "processed_articles.json"
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FEEDS_FILE = "feeds.json"
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def load_articles():
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if os.path.exists(ARTICLES_FILE):
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with open(ARTICLES_FILE, "r") as f:
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return json.load(f)
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return []
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def save_articles(articles):
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with open(ARTICLES_FILE, "w") as f:
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json.dump(articles, f, indent=2)
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def load_feeds():
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if os.path.exists(FEEDS_FILE):
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with open(FEEDS_FILE, "r") as f:
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return json.load(f)
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return []
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def save_feeds(feeds):
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with open(FEEDS_FILE, "w") as f:
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json.dump(feeds, f, indent=2)
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def fetch_and_process_feed(url):
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logging.info(f"Abrufen von Feed: {url}")
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feed = feedparser.parse(url)
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articles = load_articles()
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for entry in feed.entries:
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if any(a["link"] == entry.link for a in articles):
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continue
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try:
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images = extract_images_with_metadata(entry.link)
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except Exception as e:
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logging.warning(f"Fehler beim Bildextrakt: {e}")
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images = []
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article = {
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"id": f"{entry.link}",
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"title": entry.title,
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"summary": entry.summary,
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"link": entry.link,
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"date": entry.get("published", datetime.now().isoformat()),
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"text": entry.summary,
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"status": "New",
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"images": images,
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"tags": []
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}
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articles.append(article)
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save_articles(articles)
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def process_articles():
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feeds = load_feeds()
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for url in feeds:
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fetch_and_process_feed(url)
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def rewrite_articles():
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logging.info("Starte Umschreiben von Artikeln mit Status 'Rewrite' ...")
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articles = load_articles()
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updated = False
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for article in articles:
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if article["status"] != "Rewrite":
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continue
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try:
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prompt = f"Fasse diesen Text neu und interessant zusammen:\n\n{article['summary']}"
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response = client.chat.completions.create(
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model="gpt-4",
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messages=[{"role": "user", "content": prompt}]
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)
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rewritten = response.choices[0].message.content.strip()
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article["text"] = rewritten
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article["status"] = "Done"
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# Tags generieren
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tag_prompt = f"Erstelle passende 3-5 Tags für diesen Text:\n\n{rewritten}"
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tag_response = client.chat.completions.create(
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model="gpt-4",
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messages=[{"role": "user", "content": tag_prompt}]
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)
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tags = [tag.strip() for tag in tag_response.choices[0].message.content.split(",")]
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article["tags"] = tags
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updated = True
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logging.info(f"✅ Artikel '{article['title']}' umgeschrieben.")
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except Exception as e:
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logging.error(f"❌ Fehler beim Umschreiben von '{article['title']}':\n{e}")
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if updated:
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save_articles(articles)
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