app.py

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

WHITESPACE_HANDLER = lambda k: re.sub('\s+', ' ', re.sub('\n+', ' ', k.strip()))

# Load the mT5 model and tokenizer
model_name = "csebuetnlp/mT5_m2m_crossSum"
tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

get_lang_id = lambda lang: tokenizer._convert_token_to_id(
    model.config.task_specific_params["langid_map"][lang][1]
)

# Function for cross-lingual summarization
def cross_lingual_summarization(source_language, target_language, article_text):
    input_ids = tokenizer(
    [WHITESPACE_HANDLER(article_text)],
    return_tensors="pt",
    padding="max_length",
    truncation=True,
    max_length=512
    )["input_ids"]

    output_ids = model.generate(
    input_ids=input_ids,
    decoder_start_token_id=get_lang_id(target_language),
    max_length=84,
    no_repeat_ngram_size=2,
    num_beams=4,
    )[0]

    summary = tokenizer.decode(
    output_ids,
    skip_special_tokens=True,
    clean_up_tokenization_spaces=False
    )


    return {
        'source_language': source_language,
        'target_language': target_language,
        'original_article': article_text,
        'summary': summary
    }

# Gradio Interface
iface = gr.Interface(
    fn=cross_lingual_summarization,
    inputs=[
        gr.Dropdown(['amharic', 'arabic', 'azerbaijani', 'bengali', 'burmese', 'chinese_simplified', 'chinese_traditional',
                    'english', 'french', 'gujarati', 'hausa', 'hindi', 'igbo', 'indonesian', 'japanese', 'kirundi',
                    'korean', 'kyrgyz', 'marathi', 'nepali', 'oromo', 'pashto', 'persian', 'pidgin', 'portuguese',
                    'punjabi', 'russian', 'scottish_gaelic', 'serbian_cyrillic', 'serbian_latin', 'sinhala', 'somali',
                    'spanish', 'swahili', 'tamil', 'telugu', 'thai', 'tigrinya', 'turkish', 'ukrainian', 'urdu', 'uzbek',
                    'vietnamese', 'welsh', 'yoruba'], label='Source Language'),
        gr.Dropdown(['amharic', 'arabic', 'azerbaijani', 'bengali', 'burmese', 'chinese_simplified', 'chinese_traditional',
                    'english', 'french', 'gujarati', 'hausa', 'hindi', 'igbo', 'indonesian', 'japanese', 'kirundi',
                    'korean', 'kyrgyz', 'marathi', 'nepali', 'oromo', 'pashto', 'persian', 'pidgin', 'portuguese',
                    'punjabi', 'russian', 'scottish_gaelic', 'serbian_cyrillic', 'serbian_latin', 'sinhala', 'somali',
                    'spanish', 'swahili', 'tamil', 'telugu', 'thai', 'tigrinya', 'turkish', 'ukrainian', 'urdu', 'uzbek',
                    'vietnamese', 'welsh', 'yoruba'], label='Target Language'),
        gr.Textbox(label='Article Text')
    ],
    outputs=[
        gr.Textbox(label='Original Article'),
        gr.Textbox(label='Summary')
    ],
    live=False,
    title="Cross-Lingual Summarization"
)

# Launch the Gradio app
iface.launch(inline=False)