app.py

# Import libraries
from transformers import pipeline
import gradio as gr

# Initialize Sentiment Classification Model
model_name = 'pysentimiento/robertuito-sentiment-analysis'
classifier = pipeline("text-classification", model=model_name)

def classify_text(text):
    result = classifier(text)[0]['label']
    if result == "POS":
        return "Positivo"
    elif result == "NEG":
        return "Negativo"
    else:
        return "Neutro"

# Create Gradio Interface
input_text = gr.inputs.Textbox(label="Texto a clasificar")
output_text = gr.outputs.Textbox(label="Sentimiento")

gr.Interface(fn=classify_text, inputs=input_text, outputs=output_text, examples=[
    ['Estoy feliz 🤗 de mostrarles un toolkit para Análisis de Sentimientos y otras tareas de SocialNLP'],
    ['Espero que no lo odien.'],
    ['Lo odiamos.']
]).launch()