app.py

import re
import os
import sys

import torch
import gradio as gr
from transformers import MBart50TokenizerFast, MBartForConditionalGeneration


language_options = {
    '中文': 'zh_CN',
    '英语': 'en_XX',
    '越南语': 'vi_VN',
    '泰语': 'th_TH',
    '日语': 'ja_XX',
    '韩语': 'ko_KR',
}
languages = list(language_options.keys())

class MBartTranslator:
    """MBartTranslator class provides a simple interface for translating text using the MBart language model.

    The class can translate between 50 languages and is based on the "facebook/mbart-large-50-many-to-many-mmt"
    pre-trained MBart model. However, it is possible to use a different MBart model by specifying its name.

    Attributes:
        model (MBartForConditionalGeneration): The MBart language model.
        tokenizer (MBart50TokenizerFast): The MBart tokenizer.
    """

    def __init__(self, model_name="facebook/mbart-large-50-many-to-many-mmt", src_lang=None, tgt_lang=None):

        self.supported_languages = [
            "ar_AR",
            "cs_CZ",
            "de_DE",
            "en_XX",
            "es_XX",
            "et_EE",
            "fi_FI",
            "fr_XX",
            "gu_IN",
            "hi_IN",
            "it_IT",
            "ja_XX",
            "kk_KZ",
            "ko_KR",
            "lt_LT",
            "lv_LV",
            "my_MM",
            "ne_NP",
            "nl_XX",
            "ro_RO",
            "ru_RU",
            "si_LK",
            "tr_TR",
            "vi_VN",
            "zh_CN",
            "af_ZA",
            "az_AZ",
            "bn_IN",
            "fa_IR",
            "he_IL",
            "hr_HR",
            "id_ID",
            "ka_GE",
            "km_KH",
            "mk_MK",
            "ml_IN",
            "mn_MN",
            "mr_IN",
            "pl_PL",
            "ps_AF",
            "pt_XX",
            "sv_SE",
            "sw_KE",
            "ta_IN",
            "te_IN",
            "th_TH",
            "tl_XX",
            "uk_UA",
            "ur_PK",
            "xh_ZA",
            "gl_ES",
            "sl_SI",
        ]
        print("Building translator")
        print("Loading generator (this may take few minutes the first time as I need to download the model)")
        self.model = MBartForConditionalGeneration.from_pretrained(model_name).to(device)
        print("Loading tokenizer")
        self.tokenizer = MBart50TokenizerFast.from_pretrained(model_name, src_lang=src_lang, tgt_lang=tgt_lang)
        print("Translator is ready")

    def translate(self, text: str, input_language: str, output_language: str) -> str:
        """Translate the given text from the input language to the output language.

        Args:
            text (str): The text to translate.
            input_language (str): The input language code (e.g. "hi_IN" for Hindi).
            output_language (str): The output language code (e.g. "en_US" for English).

        Returns:
            str: The translated text.
        """
        if input_language not in self.supported_languages:
            raise ValueError(f"Input language not supported. Supported languages: {self.supported_languages}")
        if output_language not in self.supported_languages:
            raise ValueError(f"Output language not supported. Supported languages: {self.supported_languages}")

        self.tokenizer.src_lang = input_language
        encoded_input = self.tokenizer(text, return_tensors="pt").to(device)
        generated_tokens = self.model.generate(
            **encoded_input, forced_bos_token_id=self.tokenizer.lang_code_to_id[output_language]
        )
        translated_text = self.tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)

        return translated_text[0]


device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
translator = MBartTranslator()


def translate(src, dst, content):
    output = translator.translate(content, language_options[src], language_options[dst])
    # output = translator.translate(content, "zh_CN", "en_XX")
    return output

examples=[
    ['中文', '英语', '今天天气真不错！'],
    ['英语', '中文', "Life was a box of chocolates, you never know what you're gonna get."],
    ['中文', '泰语', '别放弃你的梦想，迟早有一天它会在你手里发光。'],
]

demo = gr.Interface(
    fn=translate,
    inputs=[
        gr.Dropdown(
            languages, label="源语言", value=languages[0], show_label=True
        ),
        gr.Dropdown(
            languages, label="目标语言", value=languages[1], show_label=True
        ),
        gr.Textbox(label='内容', placeholder='这里输入要翻译的内容', lines=5)
    ],
    outputs=[
        gr.Textbox(label='结果', lines=5)
    ],
    examples=examples
)


demo.launch(enable_queue=True)