app.py

import time
import gradio as gr
from transformers import pipeline 

TASK = "sentiment-analysis"
MODEL_NAME = 'cardiffnlp/twitter-roberta-base-sentiment-latest'

pipe = pipeline(TASK, model = MODEL_NAME)
MAX_CHARS = 2000

def run (text:str):
    if (text is None or not text.strip()):
        return "Ошибка: введено пустое значение!", None, None
    
    text = text.strip()
    if len(text) > MAX_CHARS:
        text = text[:MAX_CHARS]
        return 

    t0 = time.time()

    try:
        result = pipe(text)
        latency = round((time.time() - t0)*1000,1)
        return "OK", result, f"{latency} ms"
    except Exception as e:
        return f"Ошибка: {type(e).name}: {e}", None, None
        
with gr.Blocks() as demo:
    gr.Markdown( f"""" 
    # NLP-приложение (Hugging Face Spaces + Gradio)
    Задача: {TASK}
    Модель: {MODEL_NAME}
    """)
    
    inp = gr.Textbox(label = 'Введите текст', lines = 6, placeholder = "Скопируйте текст")
    btn = gr.Button("Обработать")
    status = gr.Textbox(label = 'Статус')
    out = gr.JSON(label = 'Результат модели')
    latency = gr.Textbox(label = 'Время ответа')
    
    btn.click(run,inputs = inp, outputs = [status,out,latency])
    gr.Examples(
        examples = [
            ["I love this product! It works great. "],
            ["This is the worst experience ever."],
            ["It's okay, nothing special."]          
        ],
        inputs=inp
    )

demo.launch()