KI

import nltk

from nltk.tokenize import word_tokenize

from tensorflow.keras.models import Sequential

from tensorflow.keras.layers import Dense

# NLP-Modell erstellen

nlp_model = nltk.NaiveBayesClassifier()

# Machine-Learning-Modell erstellen

ml_model = Sequential()

ml_model.add(Dense(64, activation='relu', input_shape=(100,)))

ml_model.add(Dense(64, activation='relu'))

ml_model.add(Dense(1, activation='sigmoid'))

# Kommunikationsschnittstelle erstellen

app = Flask(__name__)

@app.route('/improve_code', methods=['POST'])

def improve_code():

    code = request.get_json()['code']

    # Code analysieren und verbessern

    improved_code = ml_model.predict(code)

    return jsonify({'improved_code': improved_code})

if __name__ == '__main__':

    app.run(debug=True)