app.py

import gradio as gr
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
import torch

# Cargar el modelo
model_name = "CeciGonSer/translation_espa_pure_biblia_bart-large-cnn"  # Reemplaza esto por tu modelo en Hugging Face
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

def translate(text):
    inputs = tokenizer(text, return_tensors="pt", padding=True)
    with torch.no_grad():
        translated = model.generate(**inputs)
    translation = tokenizer.decode(translated[0], skip_special_tokens=True)
    return translation

# Interfaz Gradio
interface = gr.Interface(
    fn=translate,
    inputs=gr.Textbox(label="Introduce texto en purépecha"),
    outputs=gr.Textbox(label="Traducción al español")
)

interface.launch()