app.py

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

tokenizer = AutoTokenizer.from_pretrained("csebuetnlp/banglat5_nmt_bn_en", use_fast=False)
model = AutoModelForSeq2SeqLM.from_pretrained("csebuetnlp/banglat5_nmt_bn_en")

pipe = pipeline("translation", model=model, tokenizer=tokenizer)

def translate(text):
    translation = pipe(text)[0]['translation_text']
    return translation
interface = gr.Interface(
    fn=translate,
    inputs=gr.inputs.Textbox(label="Input Text in Bangla"),
    outputs=gr.outputs.Textbox(label="Translated Text in English"),
    title="Bangla to English Translator",
    description="Translate Bangla text into English using a Hugging Face model."
)
if __name__ == "__main__":
    interface.launch()