app.py

import gradio as gr
from transformers import pipeline

# Define the examples
examples = [
    ["в 2006-2010 гг. Вася учился в МГУ"],
    ["я купил iphone 10X за 14990 руб без 3-x часов полдень и т.д."]
]

# Load the model using Hugging Face pipeline
model = pipeline("text2text-generation", model="alexue4/text-normalization-ru-new")

# Define the function to normalize text with max_length parameter
def normalize_text(input_text):
    return model(input_text, max_length=512)[0]['generated_text']

# Create the Gradio interface
interface = gr.Interface(
    fn=normalize_text,  # The function to call
    inputs=gr.inputs.Textbox(lines=2, placeholder="Enter text here..."),  # Input type
    outputs="text",  # Output type
    examples=examples  # Examples to display
)

# Launch the interface
interface.launch()