import gradio as gr
from transformers import pipeline

summarizer_en = pipeline("summarization", model="facebook/bart-large-cnn")
summarizer_ar = pipeline("translation", model="Helsinki-NLP/opus-mt-ar-en")
translator_ar = pipeline("translation", model="Helsinki-NLP/opus-mt-en-ar")

def summarize_text(text, language):
    if not text.strip():
        return " الرجاء إدخال نص للتلخيص."
    
    if language == "العربية":

        translated_text = summarizer_ar(text)[0]['translation_text']
        summary = summarizer_en(translated_text, min_length=10, max_length=100, do_sample=False)

        final_summary = translator_ar(summary[0]['summary_text'])[0]['translation_text']
    else:
        summary = summarizer_en(text, min_length=10, max_length=100, do_sample=False)
        final_summary = summary[0]['summary_text']
    
    return final_summary

# Gradio
with gr.Blocks() as demo:
    gr.Markdown("# Text Summarization App")
    gr.Markdown("Enter a long text below, choose the language, and get a summarized version!")
    
    input_text = gr.Textbox(label="Input Text", placeholder="Enter your text here ^^ ...")
    language = gr.Dropdown(choices=["العربية", "English"], value="English", label="Select Language")
    summarize_btn = gr.Button("Summarize")
    output_text = gr.Textbox(label="Summarized Text", interactive=False)
    
    summarize_btn.click(summarize_text, inputs=[input_text, language], outputs=output_text)

if __name__ == "__main__":
    demo.launch()