app.py

from transformers import AutoTokenizer
from transformers import pipeline
import gradio as gr

# Load tokenizer and generator
tokenizer = AutoTokenizer.from_pretrained('google/mt5-base')
generator3 = pipeline(model='Suchinthana/MT5-Sinhala-Wikigen-Experimental', tokenizer=tokenizer)

# Define the function for Gradio to use
def generate_sinhala_text(prompt):
    generated_text = generator3("writeWiki:"+prompt, do_sample=True, max_length=50)[0]['generated_text']
    return generated_text

# Define the function to display loader
def loading():
    return "Loading... Please wait."

iface = gr.Interface(
    fn=generate_sinhala_text, 
    inputs=gr.Textbox(label="Topic Here"),
    outputs=gr.Textbox(lines=3, placeholder="Result Comes Here...", label="Output"),
    live=loading,  # Add the loading function here
    capture_session=True  # Add capture_session parameter
)

iface.launch()