Faktenkompass: UI-Rebrand, Admin-Assistent und Produktions-Setup.
Modernisiert die öffentliche Oberfläche mit Inter, Dark Mode und Live-Suche, ergänzt KI-gestützte Entwürfe im Admin mit Nachweis-Uploads und dokumentiert Daphne/Nginx für den Serverbetrieb. Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
Pirmin Hinderling (fedora)
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import base64
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import json
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import mimetypes
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import re
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from django.conf import settings
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from claims.models import Category, Claim
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VALID_CLAIM_STATUSES = {choice[0] for choice in Claim.Status.choices}
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VALID_EVIDENCE_LEVELS = {choice[0] for choice in Claim.EvidenceLevel.choices}
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SYSTEM_PROMPT = """Du bist ein sachlicher Fakten-Assistent für die Plattform „Faktenkompass“.
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Deine Aufgabe: Aus Artikeln, Bildern und Nutzereingaben einen überprüfbaren Fakteneintrag erstellen.
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Regeln:
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- Schreibe auf Deutsch, neutral und wissenschaftlich.
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- Keine parteipolitische Sprache, keine Übertreibungen.
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- Die Behauptung (title) formuliert eine häufig geäußerte Aussage, die überprüft wird.
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- Die Kurzantwort ist in ~20 Sekunden lesbar.
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- Quellen müssen echte, nachvollziehbare Referenzen sein (URL aus Eingabe bevorzugen).
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- Wähle eine passende bestehende Kategorie (use_existing_slug) ODER schlage eine neue vor.
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- Icons für neue Kategorien: Bootstrap Icons Klassen wie bi-thermometer-half, bi-virus, bi-lightning-charge.
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Antworte ausschließlich als gültiges JSON mit dieser Struktur:
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{
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"category": {
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"use_existing_slug": "slug-oder-null",
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"new_category": {
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"name": "Name",
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"description": "Kurzbeschreibung",
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"icon": "bi-icon-name"
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}
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},
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"claim": {
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"title": "Die zu prüfende Behauptung",
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"status": "falsch|irrefuehrend|teilweise_richtig|unbelegt|wissenschaftlicher_konsens|offene_frage",
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"short_answer": "Kurze Einordnung",
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"detailed_explanation": "Ausführlichere Erklärung",
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"evidence_level": "sehr_stark|stark|mittel|schwach"
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},
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"tags": ["Schlagwort1", "Schlagwort2"],
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"sources": [
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{
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"title": "Titel",
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"organization": "Autor/Organisation",
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"url": "https://...",
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"description": "Kurzbeschreibung"
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}
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],
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"counter_arguments": [
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{
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"argument": "Häufiges Gegenargument",
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"response": "Sachliche Antwort"
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}
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],
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"assistant_summary": "Kurze Zusammenfassung für den Admin (1-2 Sätze)"
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}
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"""
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class AIAssistantError(Exception):
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pass
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def _categories_context():
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categories = Category.objects.all().values('name', 'slug', 'description')
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if not categories:
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return 'Keine Kategorien vorhanden – neue Kategorie vorschlagen.'
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lines = []
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for cat in categories:
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lines.append(f"- {cat['name']} (slug: {cat['slug']}): {cat['description'][:120]}")
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return '\n'.join(lines)
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def _build_user_prompt(*, article_url='', article_text='', user_notes='', refinement=''):
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parts = [
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'Bestehende Kategorien:',
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_categories_context(),
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'',
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f'Artikel-URL: {article_url or "(keine)"}',
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'',
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'Artikeltext:',
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article_text or '(nicht verfügbar)',
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'',
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'Zusätzliche Hinweise des Admins:',
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user_notes or '(keine)',
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]
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if refinement:
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parts.extend(['', 'Überarbeitungswunsch:', refinement])
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return '\n'.join(parts)
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def _svg_to_png_bytes(svg_data):
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try:
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import cairosvg
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except ImportError:
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return None
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try:
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return cairosvg.svg2png(bytestring=svg_data)
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except Exception:
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return None
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def _svg_text_fallback(svg_data):
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text = svg_data.decode('utf-8', errors='replace')
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text = re.sub(r'<script[^>]*>.*?</script>', '', text, flags=re.IGNORECASE | re.DOTALL)
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return text[:4000]
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def _image_data_url(data, mime_type):
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encoded = base64.b64encode(data).decode('ascii')
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return {
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'type': 'image_url',
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'image_url': {'url': f'data:{mime_type};base64,{encoded}'},
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}
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def _image_message_part(uploaded_file):
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uploaded_file.open('rb')
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try:
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data = uploaded_file.read()
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finally:
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uploaded_file.close()
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mime_type = mimetypes.guess_type(uploaded_file.name)[0]
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if mime_type == 'application/pdf' or uploaded_file.name.lower().endswith('.pdf'):
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return {
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'type': 'text',
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'text': '[PDF-Datei hochgeladen – nutze vor allem die Admin-Beschreibung und den Artikeltext.]',
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}
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if mime_type == 'image/svg+xml' or uploaded_file.name.lower().endswith('.svg'):
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png_data = _svg_to_png_bytes(data)
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if png_data:
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return _image_data_url(png_data, 'image/png')
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return {
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'type': 'text',
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'text': (
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'[SVG-Grafik hochgeladen – OpenAI unterstützt SVG nicht direkt. '
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'Nutze diesen XML-Auszug und die Admin-Beschreibung:]\n'
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+ _svg_text_fallback(data)
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),
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}
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mime_type = mime_type or 'image/jpeg'
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if mime_type not in {'image/png', 'image/jpeg', 'image/gif', 'image/webp'}:
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mime_type = 'image/jpeg'
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return _image_data_url(data, mime_type)
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def _call_openai(messages, *, has_image=False):
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api_key = getattr(settings, 'OPENAI_API_KEY', '')
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if not api_key:
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raise AIAssistantError(
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'OPENAI_API_KEY ist nicht gesetzt. Bitte in der Umgebung oder .env konfigurieren.'
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)
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try:
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from openai import OpenAI
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except ImportError as exc:
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raise AIAssistantError('OpenAI-Paket fehlt. Bitte pip install -r requirements.txt ausführen.') from exc
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model = settings.OPENAI_MODEL_VISION if has_image else settings.OPENAI_MODEL
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client = OpenAI(api_key=api_key, timeout=settings.OPENAI_TIMEOUT)
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response = client.chat.completions.create(
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model=model,
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messages=messages,
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response_format={'type': 'json_object'},
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temperature=0.3,
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)
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content = response.choices[0].message.content
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if not content:
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raise AIAssistantError('Leere Antwort von der KI erhalten.')
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return json.loads(content)
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def _validate_payload(payload):
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claim = payload.get('claim') or {}
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status = claim.get('status', '')
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evidence = claim.get('evidence_level', '')
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if status and status not in VALID_CLAIM_STATUSES:
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raise AIAssistantError(f'Ungültiger Status von der KI: {status}')
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if evidence and evidence not in VALID_EVIDENCE_LEVELS:
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raise AIAssistantError(f'Ungültiges Evidenzlevel von der KI: {evidence}')
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return payload
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def generate_draft_payload(
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*,
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article_url='',
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article_text='',
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user_notes='',
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uploaded_file=None,
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refinement='',
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previous_payload=None,
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):
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user_prompt = _build_user_prompt(
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article_url=article_url,
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article_text=article_text,
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user_notes=user_notes,
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refinement=refinement,
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)
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if previous_payload:
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user_prompt += '\n\nBisheriger Entwurf (JSON):\n' + json.dumps(previous_payload, ensure_ascii=False)
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user_content = [{'type': 'text', 'text': user_prompt}]
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has_image = False
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extra_text = ''
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if uploaded_file and uploaded_file.name:
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part = _image_message_part(uploaded_file)
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if part.get('type') == 'image_url':
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user_content.append(part)
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has_image = True
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elif part.get('type') == 'text':
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extra_text = part['text']
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if extra_text:
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user_prompt = f'{user_prompt}\n\n{extra_text}'
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if has_image:
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user_content[0] = {'type': 'text', 'text': user_prompt}
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user_message = user_content
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else:
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user_message = user_prompt
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messages = [
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{'role': 'system', 'content': SYSTEM_PROMPT},
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{'role': 'user', 'content': user_message},
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]
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payload = _call_openai(messages, has_image=has_image)
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return _validate_payload(payload)
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def apply_payload_to_draft(draft, payload):
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category = payload.get('category') or {}
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claim = payload.get('claim') or {}
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draft.category_slug = category.get('use_existing_slug') or ''
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new_category = category.get('new_category') or {}
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draft.new_category_name = new_category.get('name', '')
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draft.new_category_description = new_category.get('description', '')
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draft.new_category_icon = new_category.get('icon', '')
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draft.title = claim.get('title', '')
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draft.claim_status = claim.get('status', Claim.Status.UNBELEGT)
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draft.short_answer = claim.get('short_answer', '')
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draft.detailed_explanation = claim.get('detailed_explanation', '')
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draft.evidence_level = claim.get('evidence_level', Claim.EvidenceLevel.MITTEL)
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draft.tags = payload.get('tags') or []
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draft.sources = payload.get('sources') or []
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draft.counter_arguments = payload.get('counter_arguments') or []
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draft.ai_raw_response = payload
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summary = payload.get('assistant_summary', 'Entwurf wurde erstellt.')
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draft.add_message('assistant', summary)
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@@ -0,0 +1,203 @@
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import ipaddress
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import re
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import socket
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from urllib.parse import urlparse
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import requests
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from bs4 import BeautifulSoup
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from django.conf import settings
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BLOCKED_HOSTNAMES = {'localhost', '127.0.0.1', '0.0.0.0', '::1'}
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MAX_DOWNLOAD_BYTES = getattr(settings, 'ARTICLE_FETCH_MAX_BYTES', 2_000_000)
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TARGET_TEXT_CHARS = getattr(settings, 'ARTICLE_FETCH_TARGET_CHARS', 8_000)
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MAX_OUTPUT_CHARS = getattr(settings, 'ARTICLE_FETCH_OUTPUT_CHARS', 12_000)
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PARTIAL_PARSE_BYTES = getattr(settings, 'ARTICLE_FETCH_PARTIAL_BYTES', 96_000)
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FETCH_TIMEOUT = getattr(settings, 'ARTICLE_FETCH_TIMEOUT', 15)
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USER_AGENT = 'FaktenkompassBot/1.0 (+https://faktenkompass.local)'
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REMOVE_TAGS = {
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'script', 'style', 'nav', 'footer', 'header', 'aside', 'noscript', 'iframe',
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'svg', 'form', 'button', 'input', 'select', 'textarea', 'menu', 'dialog',
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'figure', 'picture', 'video', 'audio', 'canvas', 'embed', 'object',
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}
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NOISE_PATTERN = re.compile(
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r'comment|sidebar|related|newsletter|cookie|banner|social|share|widget|'
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r'menu|breadcrumb|promo|advert|tracking|popup|modal|consent|paywall|'
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r'recommend|trending|tag-cloud|author-box|meta-|sharing|outbrain|taboola',
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re.IGNORECASE,
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)
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MIN_PARAGRAPH_LENGTH = 40
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class ArticleFetchError(Exception):
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pass
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def _hostname_resolves_to_private_ip(hostname):
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try:
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infos = socket.getaddrinfo(hostname, None)
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except socket.gaierror as exc:
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raise ArticleFetchError(f'Domain konnte nicht aufgelöst werden: {hostname}') from exc
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for info in infos:
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ip = ipaddress.ip_address(info[4][0])
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if (
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ip.is_private
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or ip.is_loopback
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or ip.is_link_local
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or ip.is_reserved
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or ip.is_multicast
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):
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return True
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return False
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def validate_article_url(url):
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parsed = urlparse(url.strip())
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if parsed.scheme not in {'http', 'https'}:
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raise ArticleFetchError('Nur http- und https-URLs sind erlaubt.')
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if not parsed.netloc:
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raise ArticleFetchError('Ungültige URL.')
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hostname = parsed.hostname or ''
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if hostname.lower() in BLOCKED_HOSTNAMES:
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raise ArticleFetchError('Diese URL ist nicht erlaubt.')
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if _hostname_resolves_to_private_ip(hostname):
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raise ArticleFetchError('Interne oder private URLs sind aus Sicherheitsgründen blockiert.')
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def _remove_noise_elements(soup):
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for tag_name in REMOVE_TAGS:
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for tag in soup.find_all(tag_name):
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tag.decompose()
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to_remove = []
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for element in soup.find_all(True):
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element_attrs = getattr(element, 'attrs', None) or {}
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role = element_attrs.get('role')
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if role in {'navigation', 'banner', 'complementary', 'contentinfo'}:
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to_remove.append(element)
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continue
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class_val = element_attrs.get('class', [])
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if isinstance(class_val, list):
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class_str = ' '.join(class_val)
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else:
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class_str = str(class_val or '')
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id_str = str(element_attrs.get('id', '') or '')
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combined = f'{class_str} {id_str}'.strip()
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if combined and NOISE_PATTERN.search(combined):
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to_remove.append(element)
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for element in to_remove:
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element.decompose()
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def _find_content_root(soup):
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for selector in (
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('article', {}),
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('main', {}),
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('div', {'role': 'main'}),
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('div', {'class': re.compile(r'article|content|post|entry|story', re.I)}),
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):
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tag, attrs = selector
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match = soup.find(tag, attrs=attrs) if attrs else soup.find(tag)
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if match:
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return match
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return soup.body or soup
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def _collect_paragraphs(root):
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paragraphs = []
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seen = set()
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for element in root.find_all(['h1', 'h2', 'h3', 'p', 'li', 'blockquote']):
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text = element.get_text(' ', strip=True)
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text = re.sub(r'\s+', ' ', text)
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if len(text) < MIN_PARAGRAPH_LENGTH:
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continue
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key = text.lower()
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if key in seen:
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continue
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seen.add(key)
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paragraphs.append(text)
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return paragraphs
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def _extract_readable_text(html):
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soup = BeautifulSoup(html, 'html.parser')
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_remove_noise_elements(soup)
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root = _find_content_root(soup)
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paragraphs = _collect_paragraphs(root)
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|
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if not paragraphs:
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fallback = root.get_text('\n', strip=True)
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paragraphs = []
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for line in fallback.splitlines():
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line = re.sub(r'\s+', ' ', line.strip())
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if len(line) >= MIN_PARAGRAPH_LENGTH:
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paragraphs.append(line)
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content = '\n\n'.join(paragraphs)
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content = re.sub(r'\n{3,}', '\n\n', content)
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return content.strip()
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def _finalize_text(text, *, partial=False):
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if len(text) < 100:
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raise ArticleFetchError('Aus dem Artikel konnte kein ausreichender Text extrahiert werden.')
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trimmed = text[:MAX_OUTPUT_CHARS]
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if partial and len(text) > MAX_OUTPUT_CHARS:
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trimmed += '\n\n[… Text gekürzt …]'
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return trimmed
|
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|
||||
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def _decode_html(chunks, encoding):
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return b''.join(chunks).decode(encoding or 'utf-8', errors='replace')
|
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|
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|
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def fetch_article_text(url):
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validate_article_url(url)
|
||||
try:
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response = requests.get(
|
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url,
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timeout=FETCH_TIMEOUT,
|
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headers={'User-Agent': USER_AGENT},
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allow_redirects=True,
|
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stream=True,
|
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)
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except requests.RequestException as exc:
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raise ArticleFetchError(f'Artikel konnte nicht geladen werden: {exc}') from exc
|
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|
||||
if response.status_code >= 400:
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raise ArticleFetchError(f'Artikel nicht erreichbar (HTTP {response.status_code}).')
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|
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final_host = urlparse(response.url).hostname or ''
|
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if _hostname_resolves_to_private_ip(final_host):
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raise ArticleFetchError('Weiterleitung auf eine blockierte URL.')
|
||||
|
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chunks = []
|
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size = 0
|
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encoding = response.encoding
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truncated_download = False
|
||||
|
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for chunk in response.iter_content(chunk_size=8192):
|
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if not chunk:
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||||
continue
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size += len(chunk)
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||||
if size > MAX_DOWNLOAD_BYTES:
|
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truncated_download = True
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break
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chunks.append(chunk)
|
||||
|
||||
if size >= PARTIAL_PARSE_BYTES and size % PARTIAL_PARSE_BYTES < 8192:
|
||||
text = _extract_readable_text(_decode_html(chunks, encoding))
|
||||
if len(text) >= TARGET_TEXT_CHARS:
|
||||
return _finalize_text(text, partial=True)
|
||||
|
||||
if not chunks:
|
||||
raise ArticleFetchError('Artikel konnte nicht geladen werden.')
|
||||
|
||||
text = _extract_readable_text(_decode_html(chunks, encoding))
|
||||
return _finalize_text(text, partial=truncated_download)
|
||||
@@ -0,0 +1,52 @@
|
||||
from claims.models import ClaimDraft
|
||||
from claims.services.ai_assistant import (
|
||||
AIAssistantError,
|
||||
apply_payload_to_draft,
|
||||
generate_draft_payload,
|
||||
)
|
||||
from claims.services.article_fetcher import ArticleFetchError, fetch_article_text
|
||||
|
||||
|
||||
def process_claim_draft(draft, *, refinement=''):
|
||||
draft.error_message = ''
|
||||
draft.status = ClaimDraft.DraftStatus.PROCESSING
|
||||
draft.save(update_fields=['error_message', 'status', 'updated_at'])
|
||||
|
||||
user_message_parts = []
|
||||
if draft.article_url:
|
||||
user_message_parts.append(f'Link: {draft.article_url}')
|
||||
if draft.user_notes:
|
||||
user_message_parts.append(draft.user_notes)
|
||||
if draft.uploaded_file:
|
||||
user_message_parts.append(f'Datei: {draft.uploaded_file.name}')
|
||||
if refinement:
|
||||
user_message_parts.append(f'Überarbeitung: {refinement}')
|
||||
|
||||
draft.add_message('user', '\n'.join(user_message_parts) or 'Neuer Entwurf')
|
||||
draft.save(update_fields=['conversation', 'updated_at'])
|
||||
|
||||
try:
|
||||
article_text = draft.article_text
|
||||
if draft.article_url and not refinement:
|
||||
article_text = fetch_article_text(draft.article_url)
|
||||
draft.article_text = article_text
|
||||
draft.save(update_fields=['article_text', 'updated_at'])
|
||||
|
||||
payload = generate_draft_payload(
|
||||
article_url=draft.article_url,
|
||||
article_text=article_text,
|
||||
user_notes=draft.user_notes,
|
||||
uploaded_file=draft.uploaded_file if draft.uploaded_file else None,
|
||||
refinement=refinement,
|
||||
previous_payload=draft.ai_raw_response if refinement else None,
|
||||
)
|
||||
apply_payload_to_draft(draft, payload)
|
||||
draft.status = ClaimDraft.DraftStatus.REVIEW
|
||||
draft.save()
|
||||
return draft
|
||||
except (ArticleFetchError, AIAssistantError) as exc:
|
||||
draft.status = ClaimDraft.DraftStatus.FAILED
|
||||
draft.error_message = str(exc)
|
||||
draft.add_message('assistant', f'Fehler: {exc}')
|
||||
draft.save()
|
||||
raise
|
||||
@@ -0,0 +1,103 @@
|
||||
import os
|
||||
import uuid
|
||||
|
||||
from django.db import transaction
|
||||
from django.utils.text import slugify
|
||||
|
||||
from claims.models import Category, Claim, CounterArgument, EvidenceFile, Source, Tag
|
||||
|
||||
|
||||
class DraftPublishError(Exception):
|
||||
pass
|
||||
|
||||
|
||||
def _resolve_category(draft):
|
||||
if draft.category_slug:
|
||||
category = Category.objects.filter(slug=draft.category_slug).first()
|
||||
if category:
|
||||
return category
|
||||
|
||||
if draft.new_category_name:
|
||||
category, _ = Category.objects.get_or_create(
|
||||
slug=slugify(draft.new_category_name),
|
||||
defaults={
|
||||
'name': draft.new_category_name,
|
||||
'description': draft.new_category_description or draft.new_category_name,
|
||||
'icon': draft.new_category_icon or 'bi-book',
|
||||
},
|
||||
)
|
||||
return category
|
||||
|
||||
raise DraftPublishError('Bitte eine Kategorie auswählen oder eine neue angeben.')
|
||||
|
||||
|
||||
def _get_or_create_tags(tag_names):
|
||||
tags = []
|
||||
for name in tag_names or []:
|
||||
clean = str(name).strip()
|
||||
if not clean:
|
||||
continue
|
||||
tag, _ = Tag.objects.get_or_create(name=clean, defaults={'slug': slugify(clean)})
|
||||
tags.append(tag)
|
||||
return tags
|
||||
|
||||
|
||||
@transaction.atomic
|
||||
def publish_draft(draft):
|
||||
if draft.status == draft.DraftStatus.PUBLISHED and draft.published_claim_id:
|
||||
return draft.published_claim
|
||||
|
||||
if not draft.title or not draft.short_answer:
|
||||
raise DraftPublishError('Titel und Kurzantwort sind erforderlich.')
|
||||
|
||||
category = _resolve_category(draft)
|
||||
claim = Claim.objects.create(
|
||||
category=category,
|
||||
title=draft.title,
|
||||
status=draft.claim_status or Claim.Status.UNBELEGT,
|
||||
short_answer=draft.short_answer,
|
||||
detailed_explanation=draft.detailed_explanation,
|
||||
evidence_level=draft.evidence_level or Claim.EvidenceLevel.MITTEL,
|
||||
)
|
||||
claim.tags.set(_get_or_create_tags(draft.tags))
|
||||
|
||||
for source in draft.sources or []:
|
||||
url = (source.get('url') or '').strip()
|
||||
if not url:
|
||||
continue
|
||||
Source.objects.create(
|
||||
claim=claim,
|
||||
title=source.get('title') or url,
|
||||
organization=source.get('organization') or 'Unbekannt',
|
||||
url=url,
|
||||
description=source.get('description', ''),
|
||||
)
|
||||
|
||||
for counter in draft.counter_arguments or []:
|
||||
argument = (counter.get('argument') or '').strip()
|
||||
response = (counter.get('response') or '').strip()
|
||||
if argument and response:
|
||||
CounterArgument.objects.create(claim=claim, argument=argument, response=response)
|
||||
|
||||
if draft.uploaded_file:
|
||||
_attach_uploaded_file(draft, claim)
|
||||
|
||||
draft.published_claim = claim
|
||||
draft.status = draft.DraftStatus.PUBLISHED
|
||||
draft.save(update_fields=['published_claim', 'status', 'updated_at'])
|
||||
return claim
|
||||
|
||||
|
||||
def _attach_uploaded_file(draft, claim):
|
||||
if not draft.uploaded_file:
|
||||
return
|
||||
|
||||
original_name = os.path.basename(draft.uploaded_file.name)
|
||||
ext = original_name.rsplit('.', 1)[-1].lower() if '.' in original_name else ''
|
||||
if ext not in {'jpg', 'jpeg', 'png', 'gif', 'webp', 'svg', 'pdf'}:
|
||||
return
|
||||
|
||||
evidence = EvidenceFile(claim=claim, title='')
|
||||
short_name = f'{uuid.uuid4().hex[:12]}.{ext}'
|
||||
with draft.uploaded_file.open('rb') as source_file:
|
||||
evidence.file.save(short_name, source_file, save=True)
|
||||
Reference in New Issue
Block a user