app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

# Load model and tokenizer
model_name = "VietAI/envit5-translation"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

# Translation function
def translate(text):
    input_ids = tokenizer(text, return_tensors="pt", padding=True).input_ids
    output_ids = model.generate(input_ids, max_length=512)
    return tokenizer.batch_decode(output_ids, skip_special_tokens=True)[0]

# Gradio interface
demo = gr.Interface(
    fn=translate,
    inputs="text",
    outputs="text",
    title="Vietnamese-English Translation",
    description="Translate text between English and Vietnamese using the VietAI envit5 model."
)

# Launch the Gradio app
demo.launch(debug=True)