import gradio as gr
from transformers import pipeline
import langid  # مكتبة للكشف عن اللغة


summarizer_en = pipeline("summarization", model="facebook/bart-large-cnn")
summarizer_ar = pipeline("summarization", model="malmarjeh/t5-arabic-text-summarization")

def summarize_text(text, language, min_length, max_length):
    if not text.strip():
        return "Please enter text." if language == "English" else "الرجاء إدخال نص."

    detected_language, _ = langid.classify(text)

    if detected_language == "en":
        summary = summarizer_en(
            text, 
            max_length=int(max_length), 
            min_length=int(min_length), 
            do_sample=False, 
            no_repeat_ngram_size=2
        )[0]['summary_text']
    elif detected_language == "ar":
        summary = summarizer_ar(
            text, 
            max_length=int(max_length), 
            min_length=int(min_length), 
            do_sample=False, 
            no_repeat_ngram_size=2
        )[0]['summary_text']
    else:
        return "Unsupported language."

    return summary

def translate_ui(language):
    return {
        "title": "👋 مرحبًا بك في أداة تلخيص النصوص!" if language == "العربية" else "👋 Welcome to the Text Summarization Tool!",
        "summarize_btn": " لخص النص" if language == "العربية" else " Summarize Text",
        "text_input_label": "أدخل النص" if language == "العربية" else "Enter text",
        "text_output_label": "النتيجة" if language == "العربية" else "Result",
        "min_length_label": "الحد الأدنى للطول" if language == "العربية" else "Minimum Length",
        "max_length_label": "الحد الأقصى للطول" if language == "العربية" else "Maximum Length"
    }

def update_ui(language):
    texts = translate_ui(language)
    return (
        texts["title"], 
        texts["summarize_btn"], 
        texts["text_input_label"], 
        texts["text_output_label"], 
        texts["min_length_label"], 
        texts["max_length_label"]
    )

with gr.Blocks() as demo:
    lang_toggle = gr.Radio(
        ["العربية", "English"], 
        label="🌍 اختر لغة الواجهة", 
        value="العربية", 
        elem_id="language-toggle"
    )
    title = gr.Markdown(
        "## 👋 مرحبًا بك في أداة تلخيص النصوص", 
        elem_id="title"
    )

    with gr.Row():
    
        with gr.Column():
            text_input_label = gr.Markdown(
                "أدخل النص", 
                elem_id="text-input-label"
            )
            text_input = gr.Textbox(
                label="", 
                elem_id="text-input"
            )

            min_length_label = gr.Markdown(
                "الحد الأدنى للطول", 
                elem_id="min-length-label"
            )
            min_length = gr.Slider(
                minimum=10, 
                maximum=50, 
                value=10, 
                step=1, 
                label="", 
                elem_id="min-length-slider"
            )

            max_length_label = gr.Markdown(
                "الحد الأقصى للطول", 
                elem_id="max-length-label"
            )
            max_length = gr.Slider(
                minimum=50, 
                maximum=150, 
                value=100, 
                step=1, 
                label="", 
                elem_id="max-length-slider"
            )

            summarize_btn = gr.Button(
                "لخص النص", 
                elem_id="summarize-btn", variant="primary"
            )
        
        with gr.Column():
            text_output_label = gr.Markdown(
                "النتيجة", 
                elem_id="text-output-label"
            )
            text_output = gr.Textbox(
                label="", 
                elem_id="text-output"
            )

    lang_toggle.change(
        fn=lambda lang: update_ui(lang), 
        inputs=lang_toggle,
        outputs=[
            title, 
            summarize_btn, 
            text_input_label, 
            text_output_label, 
            min_length_label, 
            max_length_label
        ]
    )

    summarize_btn.click(
        fn=summarize_text, 
        inputs=[text_input, lang_toggle, min_length, max_length], 
        outputs=text_output
    )

demo.launch()