import gradio as gr
from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
import torch

model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")

def m2m_translator(src_lang, dest_lang, text):
    tokenizer.src_lang = src_lang
    encoded = tokenizer(text, return_tensors="pt")
    generated_tokens = model.generate(**encoded, forced_bos_token_id=tokenizer.get_lang_id(dest_lang))
    response = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
    return ' '.join(response)

def greet(text):
    return m2m_translator("ru","en",text)

iface = gr.Interface(fn=greet, inputs="text", outputs="text")
iface.launch()