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Update app.py

c834f54 verified 8 months ago

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import gradio as gr
from transformers import pipeline
import PyPDF2
import re
import os
import io
import random
import time
from groq import Groq

# ==================== DEBUGGING ====================
print("=" * 50)
print("STARTING APPLICATION - ENVIRONMENT CHECK")
print("=" * 50)

# List ALL environment variables (be careful with this in production!)
print("\nAll Environment Variables:")
for key in os.environ:
    if 'KEY' in key or 'TOKEN' in key or 'SECRET' in key:
        value = os.environ[key]
        masked = value[:4] + "..." + value[-4:] if len(value) > 8 else "SET"
        print(f"  {key}: {masked}")

# ==================== IMPORT HANDLING ====================
try:
    from google import genai
    from google.genai import types
    print("\n✅ Imported google.genai successfully")
except ImportError as e:
    print(f"\n❌ Failed to import google.genai: {e}")
    genai = None
    types = None

# ==================== CONFIGURATION ====================
# Try multiple ways to get tokens
hf_token = os.environ.get("HF_TOKEN") or os.getenv("HF_TOKEN")
gemini_key = os.environ.get("GEMINI_API_KEY") or os.getenv("GEMINI_API_KEY")
groq_key = os.environ.get("GROQ_API_KEY") or os.getenv("GROQ_API_KEY")

print(f"\nToken Check:")
print(f"  HF_TOKEN: {'SET (' + hf_token[:4] + '...)' if hf_token else 'NOT SET'}")
print(f"  GEMINI_API_KEY: {'SET (' + gemini_key[:4] + '...)' if gemini_key else 'NOT SET'}")
print(f"  GROQ_API_KEY: {'SET (' + groq_key[:4] + '...)' if groq_key else 'NOT SET'}")

# ==================== GEMINI SETUP ====================
gemini_client = None
if gemini_key and genai:
    try:
        print(f"\nAttempting Gemini setup...")
        try:
            gemini_client = genai.Client(api_key=gemini_key)
            print("  ✅ Gemini client initialized with new SDK")
        except Exception as e1:
            print(f"  ⚠️ New SDK failed: {e1}")
            try:
                gemini_client = genai.client.Client(api_key=gemini_key)
                print("  ✅ Gemini client initialized with alternate method")
            except Exception as e2:
                print(f"  ⚠️ Alternate failed: {e2}")
                # Fallback to legacy
                try:
                    import google.generativeai as old_genai
                    old_genai.configure(api_key=gemini_key)
                    gemini_client = old_genai
                    print("  ✅ Using legacy google.generativeai")
                except Exception as e3:
                    print(f"  ❌ Legacy also failed: {e3}")
    except Exception as e:
        print(f"  ❌ Gemini setup error: {e}")
else:
    if not gemini_key:
        print("\n⚠️ No GEMINI_API_KEY found")
    if not genai:
        print("⚠️ Google GenAI SDK not imported")

# ==================== GROQ SETUP ====================
groq_client = None
if groq_key:
    try:
        print(f"\nAttempting Groq setup...")
        groq_client = Groq(api_key=groq_key)
        # Test the client with a simple request
        test_response = groq_client.chat.completions.create(
            messages=[{"role": "user", "content": "Hi"}],
            model="llama-3.3-70b-versatile",
            max_completion_tokens=5
        )
        print("  ✅ Groq client initialized and tested successfully")
    except Exception as e:
        print(f"  ❌ Groq setup error: {e}")
        groq_client = None
else:
    print("\n⚠️ No GROQ_API_KEY found")

print("\n" + "=" * 50)
print("SETUP COMPLETE")
print("=" * 50)

# Lazy load summarizer
summarizer = None

def load_summarizer():
    global summarizer
    if summarizer is None:
        try:
            print("Loading summarizer...")
            summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", device=-1)
            print("✅ Summarizer ready")
        except Exception as e:
            print(f"❌ Summarizer failed: {e}")
    return summarizer

# ==================== STATUS CHECK ====================
def check_status():
    statuses = []
    
    # Gemini status
    if gemini_client and gemini_key:
        statuses.append("✅ Gemini Ready")
    elif gemini_key:
        statuses.append("⚠️ Gemini key present but client failed")
    else:
        statuses.append("❌ Gemini: Add GEMINI_API_KEY")
    
    # Groq status
    if groq_client and groq_key:
        statuses.append("✅ Groq Ready")
    elif groq_key:
        statuses.append("⚠️ Groq key present but client failed")
    else:
        statuses.append("❌ Groq: Add GROQ_API_KEY")
    
    return " | ".join(statuses)

# ==================== APP 1: PDF & ESSAY TOOLS ====================

def extract_text_from_pdf(pdf_file):
    """Extract text from PDF - handle both file path and bytes"""
    if pdf_file is None:
        return None, "Please upload a PDF file."
    
    try:
        if isinstance(pdf_file, str):
            with open(pdf_file, 'rb') as f:
                pdf_reader = PyPDF2.PdfReader(f)
                text = ""
                for page in pdf_reader.pages:
                    page_text = page.extract_text()
                    if page_text:
                        text += page_text + "\n"
        else:
            if hasattr(pdf_file, 'read'):
                pdf_bytes = pdf_file.read()
                if hasattr(pdf_file, 'seek'):
                    pdf_file.seek(0)
            else:
                pdf_bytes = pdf_file
            
            if isinstance(pdf_bytes, bytes):
                pdf_stream = io.BytesIO(pdf_bytes)
            else:
                pdf_stream = io.BytesIO(pdf_bytes.encode() if isinstance(pdf_bytes, str) else pdf_bytes)
            
            pdf_reader = PyPDF2.PdfReader(pdf_stream)
            text = ""
            for page in pdf_reader.pages:
                page_text = page.extract_text()
                if page_text:
                    text += page_text + "\n"
        
        text = re.sub(r'\s+', ' ', text).strip()
        
        if len(text) < 50:
            return None, "Could not extract text. PDF may be image-based or scanned."
        
        return text, None
        
    except Exception as e:
        return None, f"Error reading PDF: {str(e)}"

def summarize_with_gemini(text, max_length, min_length):
    """Try to use Gemini for summarization"""
    if not gemini_client or not gemini_key:
        return None
    
    try:
        if hasattr(gemini_client, 'models'):
            prompt = f"Summarize the following text in {min_length}-{max_length} words. Be concise and clear:\n\n{text[:15000]}"
            
            try:
                response = gemini_client.models.generate_content(
                    model="gemini-2.5-flash",
                    contents=prompt
                )
                return response.text
            except:
                try:
                    response = gemini_client.models.generate_content(
                        model="gemini-2.5-flash",
                        contents=prompt,
                        config=types.GenerateContentConfig(
                            max_output_tokens=500
                        ) if types else None
                    )
                    return response.text
                except:
                    pass
        
        if hasattr(gemini_client, 'GenerativeModel'):
            model = gemini_client.GenerativeModel('gemini-2.5-flash')
            prompt = f"Summarize the following text in {min_length}-{max_length} words:\n\n{text[:15000]}"
            response = model.generate_content(prompt)
            return response.text
            
    except Exception as e:
        print(f"Gemini summary error: {e}")
    
    return None

def summarize_pdf(pdf_file, max_length, min_length):
    text, error = extract_text_from_pdf(pdf_file)
    if error:
        return error
    
    gemini_result = summarize_with_gemini(text, max_length, min_length)
    if gemini_result:
        return gemini_result
    
    summ = load_summarizer()
    if summ:
        try:
            result = summ(text[:3500], max_length=max_length, min_length=min_length, do_sample=False)
            return result[0]['summary_text']
        except Exception as e:
            return f"Summarization error: {str(e)}"
    
    return "Error: No summarization available"

def generate_essay_with_gemini(prompt, essay_type, word_count, tone):
    """Generate essay using Gemini"""
    if not gemini_client or not gemini_key:
        return None
    
    try:
        full_prompt = f"""You are an expert academic writer. Write a {essay_type} essay in {tone} tone.
Target length: approximately {word_count} words.
Topic: {prompt}
Requirements:
- Engaging introduction with clear thesis statement
- Well-structured body paragraphs with supporting arguments and evidence
- Strong conclusion that summarizes main points
- Use academic vocabulary and formal writing style
Write the essay now:"""
        
        if hasattr(gemini_client, 'models'):
            try:
                response = gemini_client.models.generate_content(
                    model="gemini-2.5-flash",
                    contents=full_prompt
                )
                essay = response.text.strip()
            except:
                if hasattr(gemini_client, 'GenerativeModel'):
                    model = gemini_client.GenerativeModel('gemini-2.5-flash')
                    response = model.generate_content(full_prompt)
                    essay = response.text.strip()
                else:
                    return None
        else:
            model = gemini_client.GenerativeModel('gemini-2.5-flash')
            response = model.generate_content(full_prompt)
            essay = response.text.strip()
        
        essay = re.sub(r'^#+\s*', '', essay)
        word_count_actual = len(essay.split())
        
        return f"""# {essay_type} Essay: {prompt[:50]}{'...' if len(prompt) > 50 else ''}
{essay}
---
*~{word_count_actual} words | {tone} | Gemini*"""
        
    except Exception as e:
        print(f"Essay generation error: {e}")
        return None

def generate_essay(prompt, essay_type, word_count, tone):
    if not prompt or len(prompt.strip()) < 10:
        return "Please provide a detailed prompt (at least 10 characters)."
    
    if gemini_client and gemini_key:
        gemini_result = generate_essay_with_gemini(prompt, essay_type, word_count, tone)
        if gemini_result:
            return gemini_result
    
    return f"""❌ AI generation not available.
Template Essay: {prompt}
Introduction:
{prompt} is an important topic that requires careful consideration. This essay explores its key aspects.
Body:
The significance of {prompt} cannot be overstated. Various perspectives exist on this matter, with experts debating the best approaches. Research continues to reveal new insights.
Conclusion:
In conclusion, {prompt} represents a complex issue that demands attention.
---
*Template fallback - Gemini SDK issue*
Check: 1) GEMINI_API_KEY is set 2) google-genai package is installed"""

def summarize_text(text, max_length, min_length):
    if len(text.strip()) < 100:
        return "Please provide at least 100 characters to summarize."
    
    gemini_result = summarize_with_gemini(text, max_length, min_length)
    if gemini_result:
        return gemini_result
    
    summ = load_summarizer()
    if summ:
        try:
            result = summ(text[:3500], max_length=max_length, min_length=min_length, do_sample=False)
            return result[0]['summary_text']
        except Exception as e:
            return f"Error: {str(e)}"
    
    return "Error: No summarization available"

# ==================== APP 2: QUIZ GENERATOR ====================

def extract_sentences(text):
    sentences = re.split(r'[.!?]', text)
    return [s.strip() for s in sentences if len(s.split()) > 6]

def create_quiz(text, num_questions):
    sentences = extract_sentences(text)

    if len(sentences) < num_questions:
        num_questions = len(sentences)

    selected = random.sample(sentences, num_questions)

    quiz_data = []

    for sentence in selected:
        words = sentence.split()
        keyword = random.choice(words[2:-2])

        question = sentence.replace(keyword, "_____")

        all_words = list(set(text.split()))
        wrong = random.sample(all_words, 3)

        options = wrong + [keyword]
        random.shuffle(options)

        quiz_data.append({
            "question": question,
            "options": options,
            "answer": keyword
        })

    return quiz_data

def start_quiz(text, num_questions, timer_minutes):
    if not text.strip():
        return "⚠️ Please enter study material.", None, None, None, None, None, None, ""

    quiz = create_quiz(text, num_questions)

    end_time = time.time() + (timer_minutes * 60)

    return show_question(quiz, 0, 0, end_time)

def show_question(quiz, index, score, end_time):
    if time.time() > end_time:
        return finish_quiz(score, len(quiz))

    if index >= len(quiz):
        return finish_quiz(score, len(quiz))

    q = quiz[index]

    remaining = int(end_time - time.time())

    timer_display = f"⏳ Time Left: {remaining} seconds"

    return (
        f"### Question {index+1}:\n\n{q['question']}",
        gr.update(choices=q["options"], value=None),
        f"Score: {score}",
        quiz,
        index,
        score,
        end_time,
        timer_display
    )

def submit_answer(selected, quiz, index, score, end_time):
    if selected == quiz[index]["answer"]:
        score += 1

    index += 1
    return show_question(quiz, index, score, end_time)

def finish_quiz(score, total):
    return (
        f"## ✅ Quiz Finished!\n\nFinal Score: **{score}/{total}**",
        gr.update(choices=[]),
        "",
        None,
        None,
        None,
        None,
        ""
    )

# ==================== APP 3: URDU TRANSLATOR ====================

def translate_to_urdu(text):
    """Translate English text to Urdu using Groq's Llama 3.3 70B"""
    if not text or not text.strip():
        return "Please enter some text to translate."
    
    if not groq_client:
        return "❌ Groq API not configured. Please add GROQ_API_KEY."
    
    try:
        chat_completion = groq_client.chat.completions.create(
            messages=[
                {
                    "role": "system",
                    "content": "You are a professional English to Urdu translator. Translate the given text accurately to Urdu (اردو) using natural, conversational language. Respond ONLY with the translation, no explanations."
                },
                {
                    "role": "user",
                    "content": f"Translate to Urdu:\n\n{text}"
                }
            ],
            model="llama-3.3-70b-versatile",
            temperature=0.3,
            max_completion_tokens=2048,
        )
        
        return chat_completion.choices[0].message.content
        
    except Exception as e:
        return f"Error: {str(e)}"

# ==================== CSS ====================

custom_css = """
.header { 
    text-align: center; 
    margin-bottom: 2rem; 
    padding: 2rem; 
    background: linear-gradient(135deg, #059669, #6b7280); 
    border-radius: 12px; 
    color: white; 
}
.header h1 { 
    font-size: 2.5rem; 
    margin-bottom: 0.5rem; 
}
.status-ok { 
    background: #d1fae5; 
    border: 2px solid #059669; 
    padding: 1rem; 
    border-radius: 8px; 
    text-align: center; 
    color: #065f46; 
    font-weight: bold; 
    margin-bottom: 1rem; 
}
.status-warn { 
    background: #fef3c7; 
    border: 2px solid #f59e0b; 
    padding: 1rem; 
    border-radius: 8px; 
    text-align: center; 
    color: #92400e; 
    margin-bottom: 1rem; 
}
.status-error { 
    background: #fee2e2; 
    border: 2px solid #ef4444; 
    padding: 1rem; 
    border-radius: 8px; 
    text-align: center; 
    color: #991b1b; 
    margin-bottom: 1rem; 
}
@import url('https://fonts.googleapis.com/css2?family=Noto+Nastaliq+Urdu&display=swap');
.urdu-text { 
    font-family: 'Noto Nastaliq Urdu', serif; 
    font-size: 1.5em; 
    line-height: 2; 
    direction: rtl; 
    text-align: right;
}
"""

# ==================== MAIN UI ====================

with gr.Blocks(title="Student AI Suite") as demo:
    
    # Status Display
    status = check_status()
    if "✅" in status and "❌" not in status:
        gr.HTML(f'<div class="status-ok">{status}</div>')
    elif "❌" in status:
        gr.HTML(f'<div class="status-error">{status}</div>')
    else:
        gr.HTML(f'<div class="status-warn">{status}</div>')
    
    gr.HTML('<div class="header"><h1>🎓 Student AI Suite</h1><p>Essay Generator • PDF Summarizer • Quiz Generator • Urdu Translator</p></div>')
    
    with gr.Tabs():
        
        # ==================== TAB 1: PDF & ESSAY ====================
        with gr.TabItem("📄 Essay & PDF Tools"):
            with gr.Tabs():
                with gr.TabItem("📑 PDF Summarizer"):
                    pdf_input = gr.File(label="Upload PDF", file_types=[".pdf"], type="binary")
                    with gr.Row():
                        max_len = gr.Slider(50, 500, 200, step=10, label="Max Length")
                        min_len = gr.Slider(20, 200, 50, step=10, label="Min Length")
                    summarize_btn = gr.Button("📝 Summarize PDF", variant="primary")
                    pdf_output = gr.Textbox(label="Summary", lines=12)
                    
                    gr.Markdown("---")
                    text_input = gr.Textbox(label="Or paste text", lines=5)
                    text_btn = gr.Button("Summarize Text")
                    text_output = gr.Textbox(label="Summary", lines=8)
                
                with gr.TabItem("✍️ Essay Generator"):
                    prompt_input = gr.Textbox(label="Essay Topic", placeholder="Example: 'The impact of AI on education'", lines=3)
                    essay_type = gr.Dropdown(["Argumentative", "Expository", "Descriptive", "Persuasive"], value="Argumentative")
                    tone = gr.Dropdown(["Academic", "Formal", "Neutral"], value="Academic")
                    words = gr.Slider(200, 1000, 500, step=50, label="Word Count")
                    gen_btn = gr.Button("✨ Generate Essay", variant="primary")
                    essay_output = gr.Textbox(label="Generated Essay", lines=25)
        
        # ==================== TAB 2: QUIZ GENERATOR ====================
        with gr.TabItem("🎯 Smart Quiz Generator"):
            gr.Markdown("### Paste your study text → generate quiz → test yourself!")
            
            quiz_text_input = gr.Textbox(lines=6, label="Study Material")
            
            with gr.Row():
                num_questions = gr.Slider(1, 10, value=5, step=1, label="Number of Questions")
                timer_minutes = gr.Slider(1, 10, value=2, step=1, label="Timer (Minutes)")
            
            start_btn = gr.Button("Start Quiz", variant="primary")
            
            question_box = gr.Markdown()
            options_radio = gr.Radio(label="Select Answer")
            submit_btn = gr.Button("Submit Answer", variant="secondary")
            score_display = gr.Markdown()
            timer_display = gr.Markdown()
            
            # Hidden states for quiz
            quiz_state = gr.State()
            index_state = gr.State()
            score_state = gr.State()
            endtime_state = gr.State()
        
        # ==================== TAB 3: URDU TRANSLATOR ====================
        with gr.TabItem("🌍 English to Urdu"):
            gr.Markdown("### Powered by Groq AI")
            
            with gr.Row():
                with gr.Column():
                    input_text = gr.Textbox(
                        label="English Text",
                        placeholder="Enter text to translate...",
                        lines=4
                    )
                    translate_btn = gr.Button("Translate", variant="primary")
                    
                with gr.Column():
                    output_text = gr.Textbox(
                        label="Urdu Translation (اردو)",
                        lines=4,
                        elem_classes=["urdu-text"],
                        interactive=False
                    )
            
            examples = [
                "Hello, how are you?",
                "I love Pakistan.",
                "The weather is beautiful today."
            ]
            gr.Examples(examples=examples, inputs=input_text)
    
    # ==================== EVENT HANDLERS ====================
    
    # PDF & Essay handlers
    summarize_btn.click(summarize_pdf, [pdf_input, max_len, min_len], pdf_output)
    text_btn.click(summarize_text, [text_input, max_len, min_len], text_output)
    gen_btn.click(generate_essay, [prompt_input, essay_type, words, tone], essay_output)
    
    # Quiz handlers
    start_btn.click(
        start_quiz,
        inputs=[quiz_text_input, num_questions, timer_minutes],
        outputs=[
            question_box,
            options_radio,
            score_display,
            quiz_state,
            index_state,
            score_state,
            endtime_state,
            timer_display
        ]
    )
    
    submit_btn.click(
        submit_answer,
        inputs=[options_radio, quiz_state, index_state, score_state, endtime_state],
        outputs=[
            question_box,
            options_radio,
            score_display,
            quiz_state,
            index_state,
            score_state,
            endtime_state,
            timer_display
        ]
    )
    
    # Urdu translator handlers
    translate_btn.click(fn=translate_to_urdu, inputs=input_text, outputs=output_text)
    input_text.submit(fn=translate_to_urdu, inputs=input_text, outputs=output_text)

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860, css=custom_css)

	import gradio as gr
	from transformers import pipeline
	import PyPDF2
	import re
	import os
	import io
	import random
	import time
	from groq import Groq

	# ==================== DEBUGGING ====================
	print("=" * 50)
	print("STARTING APPLICATION - ENVIRONMENT CHECK")
	print("=" * 50)

	# List ALL environment variables (be careful with this in production!)
	print("\nAll Environment Variables:")
	for key in os.environ:
	if 'KEY' in key or 'TOKEN' in key or 'SECRET' in key:
	value = os.environ[key]
	masked = value[:4] + "..." + value[-4:] if len(value) > 8 else "SET"
	print(f" {key}: {masked}")

	# ==================== IMPORT HANDLING ====================
	try:
	from google import genai
	from google.genai import types
	print("\n✅ Imported google.genai successfully")
	except ImportError as e:
	print(f"\n❌ Failed to import google.genai: {e}")
	genai = None
	types = None

	# ==================== CONFIGURATION ====================
	# Try multiple ways to get tokens
	hf_token = os.environ.get("HF_TOKEN") or os.getenv("HF_TOKEN")
	gemini_key = os.environ.get("GEMINI_API_KEY") or os.getenv("GEMINI_API_KEY")
	groq_key = os.environ.get("GROQ_API_KEY") or os.getenv("GROQ_API_KEY")

	print(f"\nToken Check:")
	print(f" HF_TOKEN: {'SET (' + hf_token[:4] + '...)' if hf_token else 'NOT SET'}")
	print(f" GEMINI_API_KEY: {'SET (' + gemini_key[:4] + '...)' if gemini_key else 'NOT SET'}")
	print(f" GROQ_API_KEY: {'SET (' + groq_key[:4] + '...)' if groq_key else 'NOT SET'}")

	# ==================== GEMINI SETUP ====================
	gemini_client = None
	if gemini_key and genai:
	try:
	print(f"\nAttempting Gemini setup...")
	try:
	gemini_client = genai.Client(api_key=gemini_key)
	print(" ✅ Gemini client initialized with new SDK")
	except Exception as e1:
	print(f" ⚠️ New SDK failed: {e1}")
	try:
	gemini_client = genai.client.Client(api_key=gemini_key)
	print(" ✅ Gemini client initialized with alternate method")
	except Exception as e2:
	print(f" ⚠️ Alternate failed: {e2}")
	# Fallback to legacy
	try:
	import google.generativeai as old_genai
	old_genai.configure(api_key=gemini_key)
	gemini_client = old_genai
	print(" ✅ Using legacy google.generativeai")
	except Exception as e3:
	print(f" ❌ Legacy also failed: {e3}")
	except Exception as e:
	print(f" ❌ Gemini setup error: {e}")
	else:
	if not gemini_key:
	print("\n⚠️ No GEMINI_API_KEY found")
	if not genai:
	print("⚠️ Google GenAI SDK not imported")

	# ==================== GROQ SETUP ====================
	groq_client = None
	if groq_key:
	try:
	print(f"\nAttempting Groq setup...")
	groq_client = Groq(api_key=groq_key)
	# Test the client with a simple request
	test_response = groq_client.chat.completions.create(
	messages=[{"role": "user", "content": "Hi"}],
	model="llama-3.3-70b-versatile",
	max_completion_tokens=5
	)
	print(" ✅ Groq client initialized and tested successfully")
	except Exception as e:
	print(f" ❌ Groq setup error: {e}")
	groq_client = None
	else:
	print("\n⚠️ No GROQ_API_KEY found")

	print("\n" + "=" * 50)
	print("SETUP COMPLETE")
	print("=" * 50)

	# Lazy load summarizer
	summarizer = None

	def load_summarizer():
	global summarizer
	if summarizer is None:
	try:
	print("Loading summarizer...")
	summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", device=-1)
	print("✅ Summarizer ready")
	except Exception as e:
	print(f"❌ Summarizer failed: {e}")
	return summarizer

	# ==================== STATUS CHECK ====================
	def check_status():
	statuses = []

	# Gemini status
	if gemini_client and gemini_key:
	statuses.append("✅ Gemini Ready")
	elif gemini_key:
	statuses.append("⚠️ Gemini key present but client failed")
	else:
	statuses.append("❌ Gemini: Add GEMINI_API_KEY")

	# Groq status
	if groq_client and groq_key:
	statuses.append("✅ Groq Ready")
	elif groq_key:
	statuses.append("⚠️ Groq key present but client failed")
	else:
	statuses.append("❌ Groq: Add GROQ_API_KEY")

	return " \| ".join(statuses)

	# ==================== APP 1: PDF & ESSAY TOOLS ====================

	def extract_text_from_pdf(pdf_file):
	"""Extract text from PDF - handle both file path and bytes"""
	if pdf_file is None:
	return None, "Please upload a PDF file."

	try:
	if isinstance(pdf_file, str):
	with open(pdf_file, 'rb') as f:
	pdf_reader = PyPDF2.PdfReader(f)
	text = ""
	for page in pdf_reader.pages:
	page_text = page.extract_text()
	if page_text:
	text += page_text + "\n"
	else:
	if hasattr(pdf_file, 'read'):
	pdf_bytes = pdf_file.read()
	if hasattr(pdf_file, 'seek'):
	pdf_file.seek(0)
	else:
	pdf_bytes = pdf_file

	if isinstance(pdf_bytes, bytes):
	pdf_stream = io.BytesIO(pdf_bytes)
	else:
	pdf_stream = io.BytesIO(pdf_bytes.encode() if isinstance(pdf_bytes, str) else pdf_bytes)

	pdf_reader = PyPDF2.PdfReader(pdf_stream)
	text = ""
	for page in pdf_reader.pages:
	page_text = page.extract_text()
	if page_text:
	text += page_text + "\n"

	text = re.sub(r'\s+', ' ', text).strip()

	if len(text) < 50:
	return None, "Could not extract text. PDF may be image-based or scanned."

	return text, None

	except Exception as e:
	return None, f"Error reading PDF: {str(e)}"

	def summarize_with_gemini(text, max_length, min_length):
	"""Try to use Gemini for summarization"""
	if not gemini_client or not gemini_key:
	return None

	try:
	if hasattr(gemini_client, 'models'):
	prompt = f"Summarize the following text in {min_length}-{max_length} words. Be concise and clear:\n\n{text[:15000]}"

	try:
	response = gemini_client.models.generate_content(
	model="gemini-2.5-flash",
	contents=prompt
	)
	return response.text
	except:
	try:
	response = gemini_client.models.generate_content(
	model="gemini-2.5-flash",
	contents=prompt,
	config=types.GenerateContentConfig(
	max_output_tokens=500
	) if types else None
	)
	return response.text
	except:
	pass

	if hasattr(gemini_client, 'GenerativeModel'):
	model = gemini_client.GenerativeModel('gemini-2.5-flash')
	prompt = f"Summarize the following text in {min_length}-{max_length} words:\n\n{text[:15000]}"
	response = model.generate_content(prompt)
	return response.text

	except Exception as e:
	print(f"Gemini summary error: {e}")

	return None

	def summarize_pdf(pdf_file, max_length, min_length):
	text, error = extract_text_from_pdf(pdf_file)
	if error:
	return error

	gemini_result = summarize_with_gemini(text, max_length, min_length)
	if gemini_result:
	return gemini_result

	summ = load_summarizer()
	if summ:
	try:
	result = summ(text[:3500], max_length=max_length, min_length=min_length, do_sample=False)
	return result[0]['summary_text']
	except Exception as e:
	return f"Summarization error: {str(e)}"

	return "Error: No summarization available"

	def generate_essay_with_gemini(prompt, essay_type, word_count, tone):
	"""Generate essay using Gemini"""
	if not gemini_client or not gemini_key:
	return None

	try:
	full_prompt = f"""You are an expert academic writer. Write a {essay_type} essay in {tone} tone.
	Target length: approximately {word_count} words.
	Topic: {prompt}
	Requirements:
	- Engaging introduction with clear thesis statement
	- Well-structured body paragraphs with supporting arguments and evidence
	- Strong conclusion that summarizes main points
	- Use academic vocabulary and formal writing style
	Write the essay now:"""

	if hasattr(gemini_client, 'models'):
	try:
	response = gemini_client.models.generate_content(
	model="gemini-2.5-flash",
	contents=full_prompt
	)
	essay = response.text.strip()
	except:
	if hasattr(gemini_client, 'GenerativeModel'):
	model = gemini_client.GenerativeModel('gemini-2.5-flash')
	response = model.generate_content(full_prompt)
	essay = response.text.strip()
	else:
	return None
	else:
	model = gemini_client.GenerativeModel('gemini-2.5-flash')
	response = model.generate_content(full_prompt)
	essay = response.text.strip()

	essay = re.sub(r'^#+\s*', '', essay)
	word_count_actual = len(essay.split())

	return f"""# {essay_type} Essay: {prompt[:50]}{'...' if len(prompt) > 50 else ''}
	{essay}
	---
	~{word_count_actual} words \| {tone} \| Gemini"""

	except Exception as e:
	print(f"Essay generation error: {e}")
	return None

	def generate_essay(prompt, essay_type, word_count, tone):
	if not prompt or len(prompt.strip()) < 10:
	return "Please provide a detailed prompt (at least 10 characters)."

	if gemini_client and gemini_key:
	gemini_result = generate_essay_with_gemini(prompt, essay_type, word_count, tone)
	if gemini_result:
	return gemini_result

	return f"""❌ AI generation not available.
	Template Essay: {prompt}
	Introduction:
	{prompt} is an important topic that requires careful consideration. This essay explores its key aspects.
	Body:
	The significance of {prompt} cannot be overstated. Various perspectives exist on this matter, with experts debating the best approaches. Research continues to reveal new insights.
	Conclusion:
	In conclusion, {prompt} represents a complex issue that demands attention.
	---
	Template fallback - Gemini SDK issue
	Check: 1) GEMINI_API_KEY is set 2) google-genai package is installed"""

	def summarize_text(text, max_length, min_length):
	if len(text.strip()) < 100:
	return "Please provide at least 100 characters to summarize."

	gemini_result = summarize_with_gemini(text, max_length, min_length)
	if gemini_result:
	return gemini_result

	summ = load_summarizer()
	if summ:
	try:
	result = summ(text[:3500], max_length=max_length, min_length=min_length, do_sample=False)
	return result[0]['summary_text']
	except Exception as e:
	return f"Error: {str(e)}"

	return "Error: No summarization available"

	# ==================== APP 2: QUIZ GENERATOR ====================

	def extract_sentences(text):
	sentences = re.split(r'[.!?]', text)
	return [s.strip() for s in sentences if len(s.split()) > 6]

	def create_quiz(text, num_questions):
	sentences = extract_sentences(text)

	if len(sentences) < num_questions:
	num_questions = len(sentences)

	selected = random.sample(sentences, num_questions)

	quiz_data = []

	for sentence in selected:
	words = sentence.split()
	keyword = random.choice(words[2:-2])

	question = sentence.replace(keyword, "_____")

	all_words = list(set(text.split()))
	wrong = random.sample(all_words, 3)

	options = wrong + [keyword]
	random.shuffle(options)

	quiz_data.append({
	"question": question,
	"options": options,
	"answer": keyword
	})

	return quiz_data

	def start_quiz(text, num_questions, timer_minutes):
	if not text.strip():
	return "⚠️ Please enter study material.", None, None, None, None, None, None, ""

	quiz = create_quiz(text, num_questions)

	end_time = time.time() + (timer_minutes * 60)

	return show_question(quiz, 0, 0, end_time)

	def show_question(quiz, index, score, end_time):
	if time.time() > end_time:
	return finish_quiz(score, len(quiz))

	if index >= len(quiz):
	return finish_quiz(score, len(quiz))

	q = quiz[index]

	remaining = int(end_time - time.time())

	timer_display = f"⏳ Time Left: {remaining} seconds"

	return (
	f"### Question {index+1}:\n\n{q['question']}",
	gr.update(choices=q["options"], value=None),
	f"Score: {score}",
	quiz,
	index,
	score,
	end_time,
	timer_display
	)

	def submit_answer(selected, quiz, index, score, end_time):
	if selected == quiz[index]["answer"]:
	score += 1

	index += 1
	return show_question(quiz, index, score, end_time)

	def finish_quiz(score, total):
	return (
	f"## ✅ Quiz Finished!\n\nFinal Score: {score}/{total}",
	gr.update(choices=[]),
	"",
	None,
	None,
	None,
	None,
	""
	)

	# ==================== APP 3: URDU TRANSLATOR ====================

	def translate_to_urdu(text):
	"""Translate English text to Urdu using Groq's Llama 3.3 70B"""
	if not text or not text.strip():
	return "Please enter some text to translate."

	if not groq_client:
	return "❌ Groq API not configured. Please add GROQ_API_KEY."

	try:
	chat_completion = groq_client.chat.completions.create(
	messages=[
	{
	"role": "system",
	"content": "You are a professional English to Urdu translator. Translate the given text accurately to Urdu (اردو) using natural, conversational language. Respond ONLY with the translation, no explanations."
	},
	{
	"role": "user",
	"content": f"Translate to Urdu:\n\n{text}"
	}
	],
	model="llama-3.3-70b-versatile",
	temperature=0.3,
	max_completion_tokens=2048,
	)

	return chat_completion.choices[0].message.content

	except Exception as e:
	return f"Error: {str(e)}"

	# ==================== CSS ====================

	custom_css = """
	.header {
	text-align: center;
	margin-bottom: 2rem;
	padding: 2rem;
	background: linear-gradient(135deg, #059669, #6b7280);
	border-radius: 12px;
	color: white;
	}
	.header h1 {
	font-size: 2.5rem;
	margin-bottom: 0.5rem;
	}
	.status-ok {
	background: #d1fae5;
	border: 2px solid #059669;
	padding: 1rem;
	border-radius: 8px;
	text-align: center;
	color: #065f46;
	font-weight: bold;
	margin-bottom: 1rem;
	}
	.status-warn {
	background: #fef3c7;
	border: 2px solid #f59e0b;
	padding: 1rem;
	border-radius: 8px;
	text-align: center;
	color: #92400e;
	margin-bottom: 1rem;
	}
	.status-error {
	background: #fee2e2;
	border: 2px solid #ef4444;
	padding: 1rem;
	border-radius: 8px;
	text-align: center;
	color: #991b1b;
	margin-bottom: 1rem;
	}
	@import url('https://fonts.googleapis.com/css2?family=Noto+Nastaliq+Urdu&display=swap');
	.urdu-text {
	font-family: 'Noto Nastaliq Urdu', serif;
	font-size: 1.5em;
	line-height: 2;
	direction: rtl;
	text-align: right;
	}
	"""

	# ==================== MAIN UI ====================

	with gr.Blocks(title="Student AI Suite") as demo:

	# Status Display
	status = check_status()
	if "✅" in status and "❌" not in status:
	gr.HTML(f'<div class="status-ok">{status}</div>')
	elif "❌" in status:
	gr.HTML(f'<div class="status-error">{status}</div>')
	else:
	gr.HTML(f'<div class="status-warn">{status}</div>')

	gr.HTML('<div class="header"><h1>🎓 Student AI Suite</h1><p>Essay Generator • PDF Summarizer • Quiz Generator • Urdu Translator</p></div>')

	with gr.Tabs():

	# ==================== TAB 1: PDF & ESSAY ====================
	with gr.TabItem("📄 Essay & PDF Tools"):
	with gr.Tabs():
	with gr.TabItem("📑 PDF Summarizer"):
	pdf_input = gr.File(label="Upload PDF", file_types=[".pdf"], type="binary")
	with gr.Row():
	max_len = gr.Slider(50, 500, 200, step=10, label="Max Length")
	min_len = gr.Slider(20, 200, 50, step=10, label="Min Length")
	summarize_btn = gr.Button("📝 Summarize PDF", variant="primary")
	pdf_output = gr.Textbox(label="Summary", lines=12)

	gr.Markdown("---")
	text_input = gr.Textbox(label="Or paste text", lines=5)
	text_btn = gr.Button("Summarize Text")
	text_output = gr.Textbox(label="Summary", lines=8)

	with gr.TabItem("✍️ Essay Generator"):
	prompt_input = gr.Textbox(label="Essay Topic", placeholder="Example: 'The impact of AI on education'", lines=3)
	essay_type = gr.Dropdown(["Argumentative", "Expository", "Descriptive", "Persuasive"], value="Argumentative")
	tone = gr.Dropdown(["Academic", "Formal", "Neutral"], value="Academic")
	words = gr.Slider(200, 1000, 500, step=50, label="Word Count")
	gen_btn = gr.Button("✨ Generate Essay", variant="primary")
	essay_output = gr.Textbox(label="Generated Essay", lines=25)

	# ==================== TAB 2: QUIZ GENERATOR ====================
	with gr.TabItem("🎯 Smart Quiz Generator"):
	gr.Markdown("### Paste your study text → generate quiz → test yourself!")

	quiz_text_input = gr.Textbox(lines=6, label="Study Material")

	with gr.Row():
	num_questions = gr.Slider(1, 10, value=5, step=1, label="Number of Questions")
	timer_minutes = gr.Slider(1, 10, value=2, step=1, label="Timer (Minutes)")

	start_btn = gr.Button("Start Quiz", variant="primary")

	question_box = gr.Markdown()
	options_radio = gr.Radio(label="Select Answer")
	submit_btn = gr.Button("Submit Answer", variant="secondary")
	score_display = gr.Markdown()
	timer_display = gr.Markdown()

	# Hidden states for quiz
	quiz_state = gr.State()
	index_state = gr.State()
	score_state = gr.State()
	endtime_state = gr.State()

	# ==================== TAB 3: URDU TRANSLATOR ====================
	with gr.TabItem("🌍 English to Urdu"):
	gr.Markdown("### Powered by Groq AI")

	with gr.Row():
	with gr.Column():
	input_text = gr.Textbox(
	label="English Text",
	placeholder="Enter text to translate...",
	lines=4
	)
	translate_btn = gr.Button("Translate", variant="primary")

	with gr.Column():
	output_text = gr.Textbox(
	label="Urdu Translation (اردو)",
	lines=4,
	elem_classes=["urdu-text"],
	interactive=False
	)

	examples = [
	"Hello, how are you?",
	"I love Pakistan.",
	"The weather is beautiful today."
	]
	gr.Examples(examples=examples, inputs=input_text)

	# ==================== EVENT HANDLERS ====================

	# PDF & Essay handlers
	summarize_btn.click(summarize_pdf, [pdf_input, max_len, min_len], pdf_output)
	text_btn.click(summarize_text, [text_input, max_len, min_len], text_output)
	gen_btn.click(generate_essay, [prompt_input, essay_type, words, tone], essay_output)

	# Quiz handlers
	start_btn.click(
	start_quiz,
	inputs=[quiz_text_input, num_questions, timer_minutes],
	outputs=[
	question_box,
	options_radio,
	score_display,
	quiz_state,
	index_state,
	score_state,
	endtime_state,
	timer_display
	]
	)

	submit_btn.click(
	submit_answer,
	inputs=[options_radio, quiz_state, index_state, score_state, endtime_state],
	outputs=[
	question_box,
	options_radio,
	score_display,
	quiz_state,
	index_state,
	score_state,
	endtime_state,
	timer_display
	]
	)

	# Urdu translator handlers
	translate_btn.click(fn=translate_to_urdu, inputs=input_text, outputs=output_text)
	input_text.submit(fn=translate_to_urdu, inputs=input_text, outputs=output_text)

	if __name__ == "__main__":
	demo.launch(server_name="0.0.0.0", server_port=7860, css=custom_css)