app/app.py aktualisiert
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app/app.py
134
app/app.py
@ -7,7 +7,7 @@ from difflib import SequenceMatcher
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app = Flask(__name__)
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# --- DB VERBINDUNG & RESET (Wie gehabt) ---
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# --- DB VERBINDUNG & RESET ---
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def get_db_connection():
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max_retries = 10
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for i in range(max_retries):
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@ -41,9 +41,30 @@ def reset_db_on_startup():
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reset_db_on_startup()
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# --- HILFSFUNKTIONEN ---
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def clean_text(text):
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"""Basis-Reinigung für Verben-Input"""
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return text.lower().strip()
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def clean_vocab_input(text):
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"""
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Spezielle Reinigung für Vokabeln:
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1. Kleinbuchstaben & Leerzeichen weg.
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2. Führendes 'to ' entfernen (damit 'go' == 'to go').
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3. Klammern entfernen (z.B. '(to)' -> weg).
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"""
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t = text.lower().strip()
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# Klammern entfernen
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t = t.replace('(', '').replace(')', '').replace('[', '').replace(']', '')
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t = t.strip()
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# Führendes "to " entfernen (nur wenn es ein ganzes Wort ist)
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if t.startswith('to '):
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t = t[3:].strip()
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return t
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def check_part(user_in, correct_str):
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variants = [x.strip().lower() for x in correct_str.split('/')]
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return user_in in variants
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@ -56,9 +77,7 @@ def index():
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@app.route('/api/pages')
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def get_pages():
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# Wir filtern jetzt nach Typ!
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mode_type = request.args.get('type', 'vocab') # 'vocab' oder 'irregular'
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mode_type = request.args.get('type', 'vocab')
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conn = get_db_connection()
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cur = conn.cursor()
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@ -77,15 +96,14 @@ def get_pages():
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@app.route('/api/question', methods=['POST'])
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def get_question():
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data = request.json
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main_mode = data.get('mainMode') # 'vocab' oder 'irregular'
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sub_mode = data.get('subMode') # 'de-en', 'start-german', etc.
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main_mode = data.get('mainMode')
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sub_mode = data.get('subMode')
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pages = data.get('pages', [])
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conn = get_db_connection()
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cur = conn.cursor()
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if main_mode == 'irregular':
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# Verben Logik
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query = "SELECT infinitive, simple_past, past_participle, german, page FROM irregular_verbs WHERE page = ANY(%s) ORDER BY RANDOM() LIMIT 1"
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cur.execute(query, (pages,))
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row = cur.fetchone()
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@ -94,22 +112,19 @@ def get_question():
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if not row: return jsonify({'error': 'Keine Verben gefunden.'})
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# Entscheiden basierend auf sub_mode
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if sub_mode == 'start-german':
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# Frage: Deutsch -> Antwort: Alle 3 Formen
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return jsonify({
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'type': 'irregular_full',
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'question': row[3], # Deutsch
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'question': row[3],
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'answer_infinitive': row[0],
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'answer_simple': row[1],
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'answer_participle': row[2],
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'page': row[4]
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})
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else:
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# Frage: Infinitiv -> Antwort: Past & Participle (Standard)
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return jsonify({
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'type': 'irregular_standard',
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'question': row[0], # Infinitive
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'question': row[0],
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'german_hint': row[3],
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'answer_simple': row[1],
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'answer_participle': row[2],
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@ -117,7 +132,6 @@ def get_question():
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})
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else:
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# Vokabel Logik
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query = "SELECT english, german, page FROM vocabulary WHERE page = ANY(%s) ORDER BY RANDOM() LIMIT 1"
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cur.execute(query, (pages,))
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row = cur.fetchone()
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@ -131,7 +145,7 @@ def get_question():
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q_text, a_text = row[1], row[0]
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elif sub_mode == 'en-de':
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q_text, a_text = row[0], row[1]
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else: # random
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else:
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if random.random() > 0.5: q_text, a_text = row[1], row[0]
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else: q_text, a_text = row[0], row[1]
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@ -147,60 +161,80 @@ def check_answer():
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data = request.json
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q_type = data.get('type')
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# 1. Verben: Alles abfragen (Start: Deutsch)
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if q_type == 'irregular_full':
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u_inf = clean_text(data.get('infinitive', ''))
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u_simp = clean_text(data.get('simple', ''))
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u_part = clean_text(data.get('participle', ''))
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# --- 1. & 2. VERBEN (Keine Typos, strikt) ---
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if q_type.startswith('irregular'):
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is_correct = False
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msg = ""
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ok_inf = check_part(u_inf, data.get('correct_infinitive', ''))
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ok_simp = check_part(u_simp, data.get('correct_simple', ''))
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ok_part = check_part(u_part, data.get('correct_participle', ''))
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if q_type == 'irregular_full':
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u_inf = clean_text(data.get('infinitive', ''))
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u_simp = clean_text(data.get('simple', ''))
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u_part = clean_text(data.get('participle', ''))
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if ok_inf and ok_simp and ok_part:
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return jsonify({'status': 'correct', 'msg': 'Perfekt! Alles richtig.'})
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else:
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sol = f"{data['correct_infinitive']} -> {data['correct_simple']} -> {data['correct_participle']}"
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return jsonify({'status': 'wrong', 'msg': f'Leider falsch. Lösung: {sol}'})
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ok_inf = check_part(u_inf, data.get('correct_infinitive', ''))
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ok_simp = check_part(u_simp, data.get('correct_simple', ''))
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ok_part = check_part(u_part, data.get('correct_participle', ''))
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# 2. Verben: Standard (Start: Infinitiv)
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elif q_type == 'irregular_standard':
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u_simp = clean_text(data.get('simple', ''))
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u_part = clean_text(data.get('participle', ''))
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if ok_inf and ok_simp and ok_part: is_correct = True
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ok_simp = check_part(u_simp, data.get('correct_simple', ''))
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ok_part = check_part(u_part, data.get('correct_participle', ''))
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elif q_type == 'irregular_standard':
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u_simp = clean_text(data.get('simple', ''))
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u_part = clean_text(data.get('participle', ''))
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if ok_simp and ok_part:
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ok_simp = check_part(u_simp, data.get('correct_simple', ''))
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ok_part = check_part(u_part, data.get('correct_participle', ''))
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if ok_simp and ok_part: is_correct = True
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if is_correct:
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return jsonify({'status': 'correct', 'msg': 'Richtig!'})
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else:
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sol = f"{data['correct_simple']} -> {data['correct_participle']}"
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return jsonify({'status': 'wrong', 'msg': f'Lösung: {sol}'})
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# Bei Verben schicken wir KEINE Lösung im msg Feld, das macht das Frontend erst am Ende
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return jsonify({'status': 'wrong', 'msg': 'Leider nicht ganz richtig.'})
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# 3. Vokabeln
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# --- 3. VOKABELN (Mit "to"-Logik und Typos) ---
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else:
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u_input = clean_text(data.get('input', ''))
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u_input_raw = data.get('input', '')
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correct_raw = data.get('correct', '')
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# Split variants (e.g. "car; auto")
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valid_answers = [clean_text(x) for x in correct_raw.split(';')]
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# Add version without brackets "(to) go" -> "go"
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for v in list(valid_answers):
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if '(' in v: valid_answers.append(v.replace('(','').replace(')','').strip())
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# Bereinigter Vergleich (ohne "to ", ohne Klammern)
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u_clean = clean_vocab_input(u_input_raw)
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if u_input in valid_answers:
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# Antwortmöglichkeiten vorbereiten (Splitten bei ';')
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valid_answers = []
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raw_parts = correct_raw.split(';')
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for p in raw_parts:
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# Original rein
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valid_answers.append(clean_vocab_input(p))
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# Falls "(to) go" drin stand -> das wird durch clean_vocab_input schon zu "go"
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# Aber falls "to go" drin stand -> wird zu "go"
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# 1. Direkter Treffer
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if u_clean in valid_answers:
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return jsonify({'status': 'correct', 'msg': 'Richtig!'})
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# Fuzzy Check
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# 2. Fuzzy Match (Rechtschreibprüfung)
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best_ratio = 0
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best_match = ""
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for v in valid_answers:
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ratio = SequenceMatcher(None, u_input, v).ratio()
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if ratio > best_ratio: best_ratio = ratio
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ratio = SequenceMatcher(None, u_clean, v).ratio()
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if ratio > best_ratio:
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best_ratio = ratio
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best_match = v # Das bereinigte Wort als Vorschlag
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if best_ratio >= 0.8:
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return jsonify({'status': 'typo', 'msg': f'Fast richtig! Lösung: {correct_raw}'})
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# Toleranz: 85% Übereinstimmung, bei kurzen Wörtern (<5 Zeichen) strenger (90%)
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threshold = 0.85
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if len(best_match) < 5:
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threshold = 0.9
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return jsonify({'status': 'wrong', 'msg': f'Falsch. Lösung: {correct_raw}'})
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if best_ratio >= threshold:
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return jsonify({
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'status': 'typo',
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'msg': f'Fast richtig! Meintest du: "{best_match}"? (Achte auf die Schreibweise)'
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})
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# 3. Falsch
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return jsonify({'status': 'wrong', 'msg': 'Leider falsch.'})
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if __name__ == '__main__':
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app.run(host='0.0.0.0', port=5000)
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