import gradio as gr
import tensorflow as tf
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.sequence import pad_sequences

model = load_model("romangpt.h5")

def generate_response(question):
    input_data = [question]
    input_sequence = pad_sequences(tokenizer.texts_to_sequences(input_data), maxlen=max_sequence_length-1)

    response = model.predict(input_sequence)[0]

    return response

iface = gr.Interface(
    fn=generate_response,
    inputs="text",
    outputs="text",
    live=True,
    title="Чат с RomanGPT",
    description="Задайте вопрос, и RomanGPT сгенерирует ответ.",
)

iface.launch()