import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
import torch
from langs import LANGS

model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-distilled-600M")
tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-200-distilled-600M")


source = 'som_Latn'
target = "eng_Latn"

def translate(source, target, text):
    translation_pipeline = pipeline("translation",
                                    model=model,
                                    tokenizer=tokenizer,
                                    src_lang=source,
                                    tgt_lang=target)

    result = translation_pipeline(text)
    return result[0]['translation_text']


gr.Interface(
    translate,
    [
        gr.components.Dropdown(label="Source Language", choices=LANGS),
        gr.components.Dropdown(label="Target Language", choices=LANGS),
        gr.components.Textbox(label="Text")
    ],
    ["text"],
).launch()