app.py

import gradio as gr
from transformers import pipeline
import torch
from diffusers import DiffusionPipeline
from datasets import load_dataset

headline_gen = pipeline("text2text-generation", model="Michau/t5-base-en-generate-headline", tokenizer="t5-base") #Headline Generator Pipeline
ar_to_en_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ar-en") #Arabic to English translator Pipeline
en_to_ar_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-ar") #English to Arabic translator Pipeline

#main function
def generate_headline(selected_language, text):
    if selected_language == "Arabic":
        translated_text = translate_ar_to_en(text)  #Translate Arabic text to English (so the headlines pipeline will understand the input)
        english_headline = generate_headline_english(translated_text) #Generate headline in English based on the translated text
        arabic_headline = translate_en_to_ar(english_headline)  # Translate headline to Arabic (output will be arabic)
        return arabic_headline

    elif selected_language == "English":
        english_headline = generate_headline_english(text) #Generate headline in English based on the text
        return english_headline

#function to translate Arabic Text to English
def translate_ar_to_en(text):
  var_ar_to_en = ar_to_en_translator(text)[0]['translation_text']
  return var_ar_to_en

#function to translate English Headline to Arabic
def translate_en_to_ar(text):
  var_en_to_ar = en_to_ar_translator(text)[0]['translation_text']
  return var_en_to_ar

#function to generate headline in english
def generate_headline_english(text):
    result1 = headline_gen(text, max_length=100, truncation=True)
    result2 = result1[0]['generated_text']
    return result2


examples = [
    ["Arabic", "تعتبر انبعاثات الغازات الدفيئة، مثل ثاني أكسيد الكربون (CO2) والميثان (CH4)، من الأسباب الرئيسية لتغير المناخ العالمي. تؤدي الأنشطة البشرية، مثل حرق الوقود الأحفوري لإنتاج الطاقة وإزالة الغابات والعمليات الصناعية، إلى زيادة كبيرة في تركيز هذه الغازات في الغلاف الجوي. وفقًا للهيئة الحكومية الدولية المعنية بتغير المناخ (IPCC)، ارتفعت مستويات ثاني أكسيد الكربون بأكثر من 50٪ منذ عصر ما قبل الصناعة، مما ساهم في ارتفاع درجات الحرارة العالمية."],
    ["English", "Greenhouse gas emissions, primarily carbon dioxide (CO2) and methane (CH4), are the main drivers of global climate change. Human activities, such as burning fossil fuels for energy, deforestation, and industrial processes, have significantly increased the concentration of these gases in the atmosphere. According to the Intergovernmental Panel on Climate Change (IPCC), CO2 levels have risen by over 50% since the pre-industrial era, contributing to rising global temperatures."]
]

custom_css = """
body {
    background-color: #f4f4f9;
    color: #333;
}
.gradio-container {
    border-radius: 10px;
    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
    background-color: #fff;
}
label {
    color: #9B59B6;  
    font-weight: bold;
}
input[type="text"], textarea {
    border: 1px solid #9B59B6;  
}
textarea {
    height: 150px;
}
button {
    background-color: #9B59B6;  
    color: #fff;
    border-radius: 5px;
    cursor: pointer;
}
button:hover {
    background-color: #8E44AD; 
}
.dropdown {
    border: 1px solid #9B59B6;  
    border-radius: 4px;
}
"""

interface = gr.Interface(
    fn=generate_headline,
    inputs=[
        gr.Dropdown(choices=["Arabic", "English"], label="Select Language"),
        gr.Textbox(lines=5, placeholder="Enter article text here", label="Text/Article") 
    ],
    outputs=gr.Textbox(label="Generated Headline"),

    examples=examples,
    css=custom_css  
)

interface.launch()