app.py

import gradio as gr
from NDETCStemmer import NDETCStemmer

num_text_process_limit = 100
markdown_top_info = """
# [NDETCStemmer](https://huggingface.co/kaenova/NDETCStemmer) spaces
Easily use the model with huggingface 🤗 and gradio interface!  
Call by API is also available. Check the bottom of the page on 'Use via API 🚀'
"""

stemmer = NDETCStemmer()
process_counter = 0

def process_single_text(text_input: "str"):
    
    # Split input
    if text_input.strip() == "":
        return ""
    results = stemmer.stem(text_input)
    
    # Logging
    global process_counter
    process_counter = process_counter + 1
    
    print(f"INFO: Number of processed text {process_counter}")
    
    return results

with gr.Blocks() as demo:
    gr.Markdown(markdown_top_info)

    # Single Input
    with gr.Column():
        input_text = gr.Textbox(
            label="Input Text",
            info=f"Text to stem.",
            lines=5,
            value="""bibirnya memerah tangannya jadi selengket madu dan ia berkata 'Boleh saya memerah lembu ini?'""",
        )
        single_text_button = gr.Button("Stem!")
        results_text = gr.Textbox(
            label=f"Result",
            interactive=False,
        )
        single_text_button.click(
            process_single_text,
            inputs=[input_text],
            outputs=[results_text],
            api_name="process"
        )

if __name__ == "__main__":
    demo.queue(concurrency_count=100)
    demo.launch()