app.py

import os
import gradio as gr
import pdfplumber
from openai import OpenAI
from langdetect import detect

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

SUMMARY_STYLES = ["Child-Friendly", "Academic", "Tweet"]
LANGUAGES = ["English", "Turkish", "French", "German", "Spanish", "Arabic"]

LANGUAGE_CODES = {
    "English": "en",
    "Turkish": "tr",
    "French": "fr",
    "German": "de",
    "Spanish": "es",
    "Arabic": "ar"  
}

QUIZ_TITLES = {
    "English": "### 📘 Quiz Questions:",
    "Turkish": "### 📘 Test Soruları:",
    "French": "### 📘 Questions à Choix Multiples :",
    "German": "### 📘 Quizfragen:",
    "Spanish": "### 📘 Preguntas del cuestionario:",
    "Arabic": "### 📘 أسئلة الاختيار من متعدد:"
}

PROMPT_TEMPLATES = {
    "English": "Please summarize the following text in a {style} style and keep it within approximately {char_limit} characters.\nThen provide 5 relevant keywords.\n\nTEXT:\n{text}",
    "Turkish": "Lütfen aşağıdaki metni {style} tarzında ve yaklaşık {char_limit} karakter olacak şekilde özetle.\nArdından 5 anahtar kelime ver.\n\nMETİN:\n{text}",
    "French": "Veuillez résumer le texte suivant dans un style {style}, en environ {char_limit} caractères.\nFournissez ensuite 5 mots-clés pertinents.\n\nTEXTE :\n{text}",
    "German": "Fassen Sie den folgenden Text im {style}-Stil mit etwa {char_limit} Zeichen zusammen.\nGeben Sie anschließend 5 relevante Schlüsselwörter an.\n\nTEXT:\n{text}",
    "Spanish": "Resume el siguiente texto en un estilo {style} y con un límite de aproximadamente {char_limit} caracteres.\nLuego proporciona 5 palabras clave relevantes.\n\nTEXTO:\n{text}",
    "Arabic": "الرجاء تلخيص النص التالي بأسلوب {style}، على ألا يتجاوز {char_limit} حرفًا.\nثم قدم 5 كلمات مفتاحية مهمة.\n\nالنص:\n{text}"
}

QUIZ_PROMPTS = {
    "English": "Based on the text below, generate 2 multiple choice questions (each with 4 options A-D):\n\n{text}",
    "Turkish": "Aşağıdaki metne dayanarak, 4 seçenekli (A, B, C, D) 2 adet çoktan seçmeli soru oluştur:\n\n{text}",
    "French": "Sur la base du texte ci-dessous, générez 2 questions à choix multiples (4 options A à D) :\n\n{text}",
    "German": "Erstelle basierend auf dem folgenden Text 2 Multiple-Choice-Fragen (mit jeweils 4 Optionen A–D):\n\n{text}",
    "Spanish": "Con base en el siguiente texto, genera 2 preguntas de opción múltiple (cada una con 4 opciones A–D):\n\n{text}",
    "Arabic": "قم بإنشاء سؤالين اختيار من متعدد استنادًا إلى النص أدناه، مع أربعة خيارات لكل سؤال (أ، ب، ج، د):\n\n{text}"
}

def extract_text_from_pdf(file):
    try:
        with pdfplumber.open(file.name) as pdf:
            text = ""
            for page in pdf.pages:
                page_text = page.extract_text()
                if page_text:
                    text += page_text + "\n"
        return text.strip() if text.strip() else None, None
    except Exception as e:
        return None, str(e)

def translate_text(text, target_lang):
    prompt = f"Translate the following text into {target_lang}:\n\n{text}"
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.3,
        max_tokens=1000
    )
    return response.choices[0].message.content

def replace_arabic_choices(quiz_text):
    return quiz_text.replace("A)", "أ.").replace("B)", "ب.").replace("C)", "ج.").replace("D)", "د.")

def generate_summary_and_keywords(text, summary_lang, style, char_limit):
    template = PROMPT_TEMPLATES[summary_lang]
    prompt = template.format(style=style, char_limit=char_limit, text=text[:2000])
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.7,
        max_tokens=700
    )
    return response.choices[0].message.content

def generate_quiz(summary_text, summary_lang):
    prompt = QUIZ_PROMPTS[summary_lang].format(text=summary_text)
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.7,
        max_tokens=500
    )
    result = response.choices[0].message.content
    return replace_arabic_choices(result) if summary_lang == "Arabic" else result

def process(text_input, pdf_file, summary_lang, style, char_limit, make_quiz):
    if not char_limit.isdigit():
        return "⚠️ Please enter a numeric character limit."

    text, error = extract_text_from_pdf(pdf_file) if pdf_file else (text_input.strip(), None)
    if error or not text:
        return f"⚠️ Error: {error or 'No valid text provided.'}"

    detected = detect(text)
    if detected != LANGUAGE_CODES[summary_lang]:
        text = translate_text(text, summary_lang)

    summary = generate_summary_and_keywords(text, summary_lang, style, char_limit)
    if make_quiz:
        quiz = generate_quiz(summary, summary_lang)
        return summary + "\n\n" + QUIZ_TITLES[summary_lang] + "\n" + quiz
    return summary

with gr.Blocks(css="""
.big-file-upload .file-wrap, 
.big-file-upload .wrap, 
.big-file-upload .upload-box, 
.big-file-upload .dropbox {
    min-height: 258px !important;
    max-height: 258px !important;
    height: 258px !important;
}
.big-textbox textarea {
    min-height: 210px !important;
    max-height: 210px !important;
    height: 210px !important;
}
""") as demo:
    gr.Markdown("## 🌍 Multilingual Summarizer + Quiz Generator")

    with gr.Accordion("📘 View README / Usage Guide", open=False):
        gr.Markdown("""
This application allows you to upload a PDF or paste text, select your preferred summary language, and receive:
- ✂️ A clear summary  
- 🏷️ An auto-generated title  
- 🔑 5 relevant keywords  
- 🌐 If the content language and summary language differ, the app will auto-translate before summarizing  
Powered by OpenAI GPT-3.5 and Gradio.
""")

    with gr.Row():
        summary_lang = gr.Dropdown(LANGUAGES, value="English", label="Summary Language")
        summary_style = gr.Dropdown(SUMMARY_STYLES, value="Academic", label="Summary Style")
        char_limit = gr.Textbox(label="Character Limit", value="300")

    make_quiz = gr.Checkbox(label="Generate Quiz Questions", value=True)

    with gr.Row():
        with gr.Column(scale=2):
            text_input = gr.Textbox(lines=15, label="Text Input", elem_classes="big-textbox")
        with gr.Column(scale=2):
            pdf_file = gr.File(label="Or Upload PDF", elem_classes="big-file-upload")

    output = gr.Textbox(label="Output", lines=8)

    run_btn = gr.Button("Summarize")

    run_btn.click(
        inputs=[summary_lang, summary_style, char_limit, text_input, pdf_file, make_quiz],
        outputs=output
    )

demo.launch()