import gradio as gr
from transformers import pipeline

# Escolha um modelo menor para evitar sobrecarga
model_name = "google/flan-t5-small"  # Modelo exemplo
pipe = pipeline("text2text-generation", model=model_name)

def generate_text(prompt):
    return pipe(prompt)[0]['generated_text']

iface = gr.Interface(
    fn=generate_text,
    inputs="text",
    outputs="text",
    title="Text Generation API",
    description="Gera texto a partir de um prompt usando um modelo Hugging Face."
)

if __name__ == "__main__":
    iface.launch(server_name="0.0.0.0", server_port=8080)