import tensorflow as tf from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense # Создание model = Sequential() model.add(Dense(64, input_dim=10, activation='relu')) model.add(Dense(1, activation='sigmoid')) # Компиляция model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) # Обучение model.fit(X_train, y_train, epochs=10, batch_size=10, validation_data=(X_test, y_test)) import openai openai.api_key = 'ваш_ключ_API' response = openai.Completion.create( engine="davinci", prompt="Сгенерируй текст на тему ИИ", max_tokens=50 ) print(response.choices[0].text.strip()) from flask import Flask, request, jsonify import tensorflow as tf app = Flask(__name__) # Загрузка модели model = tf.keras.models.load_model('path/to/your/model') @app.route('/predict', methods=['POST']) def predict(): data = request.get_json(force=True) prediction = model.predict(data['input']) return jsonify({'prediction': prediction.tolist()}) if __name__ == '__main__': app.run(debug=True)