Create app.py

app.py

@@ -0,0 +1,878 @@
+import os
+import tempfile
+
+# ✅ CRITICAL: Set environment variables BEFORE any other imports
+os.environ['TRANSFORMERS_CACHE'] = tempfile.gettempdir()
+os.environ['HF_HOME'] = tempfile.gettempdir()
+os.environ['TORCH_HOME'] = tempfile.gettempdir()
+os.environ['HF_DATASETS_CACHE'] = tempfile.gettempdir()
+os.environ['HUGGINGFACE_HUB_CACHE'] = tempfile.gettempdir()
+
+import streamlit as st
+
+# ✅ CRITICAL: set_page_config() MUST be called first, before ANY Streamlit commands
+st.set_page_config(
+    page_title="AI Study Helper Pro - by Umaima Qureshi",
+    page_icon="🧠",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Now import other libraries
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM, AutoModelForQuestionAnswering, AutoModelForSequenceClassification
+from nltk.tokenize import sent_tokenize
+import base64
+import torch
+import nltk
+
+@st.cache_resource
+def init_nltk():
+    """Initialize NLTK with writable directory"""
+    nltk_data_dir = os.path.join(tempfile.gettempdir(), "nltk_data")
+    os.makedirs(nltk_data_dir, exist_ok=True)
+    
+    if nltk_data_dir not in nltk.data.path:
+        nltk.data.path.insert(0, nltk_data_dir)
+    
+    for pkg in ["punkt", "punkt_tab"]:
+        try:
+            nltk.data.find(f"tokenizers/{pkg}")
+        except LookupError:
+            try:
+                nltk.download(pkg, download_dir=nltk_data_dir, quiet=True)
+            except:
+                pass  # Continue if download fails
+    
+    return True
+
+# Initialize NLTK
+init_nltk()
+
+# Device detection
+DEVICE = 0 if torch.cuda.is_available() else -1
+
+# Lazy model loading with proper cache handling - FIXED (No cache_dir in pipeline)
+@st.cache_resource
+def get_summarizer():
+    """Load summarization model - cache_dir handled by environment variables"""
+    try:
+        model = AutoModelForSeq2SeqLM.from_pretrained(
+            "sshleifer/distilbart-cnn-12-6",
+            cache_dir=tempfile.gettempdir()
+        )
+        tokenizer = AutoTokenizer.from_pretrained(
+            "sshleifer/distilbart-cnn-12-6",
+            cache_dir=tempfile.gettempdir()
+        )
+        summarizer = pipeline(
+            "summarization",
+            model=model,
+            tokenizer=tokenizer,
+            device=DEVICE
+        )
+        return summarizer
+    except Exception as e:
+        st.error(f"Failed to load summarizer: {str(e)}")
+        return None
+
+@st.cache_resource
+def get_qa():
+    """Load Q&A model - cache_dir handled by environment variables"""
+    try:
+        model = AutoModelForQuestionAnswering.from_pretrained(
+            "distilbert-base-uncased-distilled-squad",
+            cache_dir=tempfile.gettempdir()
+        )
+        tokenizer = AutoTokenizer.from_pretrained(
+            "distilbert-base-uncased-distilled-squad",
+            cache_dir=tempfile.gettempdir()
+        )
+        qa_pipeline = pipeline(
+            "question-answering",
+            model=model,
+            tokenizer=tokenizer,
+            device=DEVICE
+        )
+        return qa_pipeline
+    except Exception as e:
+        st.error(f"Failed to load Q&A model: {str(e)}")
+        return None
+
+@st.cache_resource
+def get_classifier():
+    """Load classifier model - cache_dir handled by environment variables"""
+    try:
+        model = AutoModelForSequenceClassification.from_pretrained(
+            "typeform/distilbert-base-uncased-mnli",
+            cache_dir=tempfile.gettempdir()
+        )
+        tokenizer = AutoTokenizer.from_pretrained(
+            "typeform/distilbert-base-uncased-mnli",
+            cache_dir=tempfile.gettempdir()
+        )
+        classifier = pipeline(
+            "zero-shot-classification",
+            model=model,
+            tokenizer=tokenizer,
+            device=DEVICE
+        )
+        return classifier
+    except Exception as e:
+        st.error(f"Failed to load classifier: {str(e)}")
+        return None
+
+@st.cache_resource
+def load_translator(model_name):
+    """Load translation model - cache_dir handled by environment variables"""
+    try:
+        model = AutoModelForSeq2SeqLM.from_pretrained(
+            model_name,
+            cache_dir=tempfile.gettempdir()
+        )
+        tokenizer = AutoTokenizer.from_pretrained(
+            model_name,
+            cache_dir=tempfile.gettempdir()
+        )
+        translator = pipeline(
+            "translation",
+            model=model,
+            tokenizer=tokenizer,
+            device=DEVICE
+        )
+        return translator
+    except Exception as e:
+        st.error(f"Failed to load translator: {str(e)}")
+        return None
+
+def truncate_text(text, max_words=400):
+    """Truncate text to maximum word count"""
+    words = text.split()
+    return (" ".join(words[:max_words]), len(words) > max_words)
+
+# ULTRA PREMIUM CSS - Glassmorphism + Animations
+st.markdown("""
+<style>
+@import url('https://fonts.googleapis.com/css2?family=Poppins:wght@300;400;600;700;900&display=swap');
+
+* {
+    font-family: 'Poppins', sans-serif;
+}
+
+.stApp {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 25%, #f093fb 50%, #4facfe 75%, #00f2fe 100%);
+    background-size: 400% 400%;
+    animation: gradientShift 15s ease infinite;
+}
+
+@keyframes gradientShift {
+    0% { background-position: 0% 50%; }
+    50% { background-position: 100% 50%; }
+    100% { background-position: 0% 50%; }
+}
+
+/* Hero Header */
+.hero-header {
+    background: linear-gradient(135deg, #1e1e3f 0%, #2d2d5f 100%);
+    padding: 3rem 2rem;
+    border-radius: 25px;
+    margin-bottom: 2rem;
+    text-align: center;
+    box-shadow: 0 20px 60px rgba(0, 0, 0, 0.5);
+    border: 2px solid #667eea;
+}
+
+.hero-title {
+    font-size: 3.5rem;
+    font-weight: 900;
+    color: #ffffff;
+    margin: 0 0 1rem 0;
+    text-shadow: 2px 2px 8px rgba(0, 0, 0, 0.5);
+}
+
+.hero-subtitle {
+    font-size: 1.3rem;
+    color: #ffffff;
+    margin: 0;
+    font-weight: 400;
+    opacity: 0.95;
+}
+
+/* Premium Tabs */
+.stTabs [data-baseweb="tab-list"] {
+    gap: 12px;
+    background: rgba(255, 255, 255, 0.1);
+    padding: 12px;
+    border-radius: 20px;
+    backdrop-filter: blur(10px);
+    border: 1px solid rgba(255, 255, 255, 0.2);
+}
+
+.stTabs [data-baseweb="tab"] {
+    background: rgba(255, 255, 255, 0.15);
+    border-radius: 15px;
+    color: white;
+    font-weight: 600;
+    font-size: 1.1rem;
+    padding: 12px 24px;
+    border: 1px solid rgba(255, 255, 255, 0.25);
+    transition: all 0.3s ease;
+    text-shadow: 0 2px 4px rgba(0, 0, 0, 0.2);
+}
+
+.stTabs [data-baseweb="tab"]:hover {
+    background: rgba(255, 255, 255, 0.25);
+    transform: translateY(-2px);
+    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.2);
+}
+
+.stTabs [aria-selected="true"] {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    border-color: rgba(255, 255, 255, 0.4);
+    box-shadow: 0 8px 24px rgba(102, 126, 234, 0.4);
+}
+
+/* Premium Buttons */
+.stButton > button {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+    font-weight: 700;
+    font-size: 1.1rem;
+    padding: 16px 40px;
+    border-radius: 16px;
+    border: none;
+    box-shadow: 0 8px 24px rgba(102, 126, 234, 0.4);
+    transition: all 0.3s ease;
+    width: 100%;
+    text-shadow: 0 2px 4px rgba(0, 0, 0, 0.2);
+}
+
+.stButton > button:hover {
+    transform: translateY(-3px);
+    box-shadow: 0 12px 36px rgba(102, 126, 234, 0.6);
+    background: linear-gradient(135deg, #764ba2 0%, #667eea 100%);
+}
+
+.stButton > button:active {
+    transform: translateY(-1px);
+}
+
+/* Input Fields - FIXED: Black background for text areas */
+.stTextArea textarea, .stTextInput input {
+    background: rgba(0, 0, 0, 0.85) !important;
+    backdrop-filter: blur(10px);
+    border: 2px solid rgba(255, 255, 255, 0.3) !important;
+    border-radius: 16px !important;
+    color: white !important;
+    font-size: 1rem !important;
+    padding: 16px !important;
+    text-shadow: 0 1px 2px rgba(0, 0, 0, 0.2);
+}
+
+.stTextArea textarea::placeholder, .stTextInput input::placeholder {
+    color: rgba(255, 255, 255, 0.6) !important;
+}
+
+.stTextArea textarea:focus, .stTextInput input:focus {
+    border-color: rgba(255, 255, 255, 0.6) !important;
+    box-shadow: 0 0 20px rgba(255, 255, 255, 0.3) !important;
+    background: rgba(0, 0, 0, 0.9) !important;
+}
+
+/* Result Cards */
+.result-card {
+    background: rgba(255, 255, 255, 0.95);
+    color: #1a1a1a;
+    padding: 2rem;
+    border-radius: 20px;
+    margin: 1rem auto;
+    max-width: 900px;
+    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.2);
+    animation: fadeIn 0.5s ease;
+    border-left: 5px solid #667eea;
+}
+
+.result-card p {
+    word-break: break-word;
+    overflow-wrap: break-word;
+    max-height: 200px;
+    overflow-y: auto;
+    line-height: 1.6;
+}
+
+/* FIXED: Scrollable container for keywords with proper visibility */
+.keywords-container {
+    max-height: 400px;
+    overflow-y: auto;
+    padding: 10px;
+    background: rgba(255, 255, 255, 0.05);
+    border-radius: 15px;
+    margin-top: 1rem;
+}
+
+/* FIXED: Quiz questions container with dark background and scrolling */
+.quiz-container {
+    max-height: 500px;
+    overflow-y: auto;
+    padding: 10px;
+}
+
+.quiz-question-card {
+    background: rgba(30, 30, 60, 0.9) !important;
+    color: white !important;
+    padding: 1.5rem;
+    margin: 1rem 0;
+    border-radius: 15px;
+    border-left: 4px solid #667eea;
+    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.3);
+}
+
+.quiz-question-card strong {
+    color: #667eea !important;
+}
+
+@keyframes fadeIn {
+    from { opacity: 0; transform: translateY(20px); }
+    to { opacity: 1; transform: translateY(0); }
+}
+
+/* Stats Badge */
+.stats-badge {
+    display: inline-block;
+    background: rgba(255, 255, 255, 0.25);
+    backdrop-filter: blur(10px);
+    padding: 8px 20px;
+    border-radius: 20px;
+    color: white;
+    font-weight: 600;
+    border: 1px solid rgba(255, 255, 255, 0.3);
+    margin: 5px;
+    text-shadow: 0 1px 3px rgba(0, 0, 0, 0.3);
+}
+
+/* Success/Error Messages */
+.stSuccess {
+    background: rgba(72, 187, 120, 0.25) !important;
+    backdrop-filter: blur(10px);
+    border-left: 4px solid #48bb78 !important;
+    border-radius: 12px !important;
+    color: white !important;
+}
+
+.stError {
+    background: rgba(245, 101, 101, 0.25) !important;
+    backdrop-filter: blur(10px);
+    border-left: 4px solid #f56565 !important;
+    border-radius: 12px !important;
+    color: white !important;
+}
+
+.stInfo {
+    background: rgba(66, 153, 225, 0.25) !important;
+    backdrop-filter: blur(10px);
+    border-left: 4px solid #4299e1 !important;
+    border-radius: 12px !important;
+    color: white !important;
+}
+
+.stWarning {
+    background: rgba(237, 137, 54, 0.25) !important;
+    backdrop-filter: blur(10px);
+    border-left: 4px solid #ed8936 !important;
+    border-radius: 12px !important;
+    color: white !important;
+}
+
+/* Sidebar */
+.css-1d391kg, [data-testid="stSidebar"] {
+    background: rgba(20, 20, 40, 0.9);
+    backdrop-filter: blur(20px);
+    border-right: 1px solid rgba(255, 255, 255, 0.2);
+}
+
+.css-1d391kg h2, [data-testid="stSidebar"] h2 {
+    color: white;
+    font-weight: 700;
+    text-shadow: 0 2px 4px rgba(0, 0, 0, 0.3);
+}
+
+.css-1d391kg p, [data-testid="stSidebar"] p {
+    color: rgba(255, 255, 255, 0.9);
+}
+
+/* Ensure text wraps properly */
+.stTabs h3 {
+    word-break: break-word;
+    overflow-wrap: anywhere;
+    white-space: normal;
+    max-width: 100%;
+    margin: 0;
+    padding: 0.5rem 0;
+    color: white;
+    text-shadow: 0 2px 4px rgba(0, 0, 0, 0.3);
+}
+
+/* Spinner */
+.stSpinner > div {
+    border-top-color: white !important;
+}
+
+/* Selectbox */
+.stSelectbox > div > div {
+    background: rgba(255, 255, 255, 0.2) !important;
+    backdrop-filter: blur(10px);
+    border-radius: 12px !important;
+    color: white !important;
+    border: 2px solid rgba(255, 255, 255, 0.3) !important;
+}
+
+.stSelectbox label {
+    color: white !important;
+    font-weight: 600 !important;
+    text-shadow: 0 1px 3px rgba(0, 0, 0, 0.3);
+}
+
+/* Footer */
+.premium-footer {
+    text-align: center;
+    padding: 2rem;
+    margin-top: 3rem;
+    background: rgba(20, 20, 40, 0.85);
+    backdrop-filter: blur(15px);
+    border-radius: 20px;
+    border: 2px solid rgba(255, 255, 255, 0.3);
+    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.3);
+}
+
+.premium-footer p {
+    color: rgba(255, 255, 255, 0.9);
+    margin: 0.5rem 0;
+    text-shadow: 0 1px 3px rgba(0, 0, 0, 0.3);
+}
+
+/* Hide Streamlit Branding */
+#MainMenu {visibility: hidden;}
+footer {visibility: hidden;}
+header {visibility: hidden;}
+
+/* Custom scrollbar */
+::-webkit-scrollbar {
+    width: 10px;
+}
+
+::-webkit-scrollbar-track {
+    background: rgba(255, 255, 255, 0.1);
+}
+
+::-webkit-scrollbar-thumb {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    border-radius: 5px;
+}
+
+::-webkit-scrollbar-thumb:hover {
+    background: linear-gradient(135deg, #764ba2 0%, #667eea 100%);
+}
+</style>
+""", unsafe_allow_html=True)
+
+# Hero Header
+st.markdown("""
+<div class="hero-header">
+    <div class="hero-title">🧠 AI Study Helper Pro</div>
+    <div class="hero-subtitle">⚡ Supercharge Your Learning with Advanced AI Technology</div>
+</div>
+""", unsafe_allow_html=True)
+
+# Add cache clear button (for troubleshooting)
+with st.expander("⚙️ Settings", expanded=False):
+    if st.button("🔄 Clear Model Cache (if you see errors)"):
+        st.cache_resource.clear()
+        st.success("✅ Cache cleared! Please refresh the page.")
+        st.info("💡 This will reload all AI models on next use.")
+
+# Sidebar
+with st.sidebar:
+    st.markdown("### 🎯 Dashboard")
+    st.markdown("---")
+    
+    # Stats
+    col1, col2 = st.columns(2)
+    with col1:
+        st.markdown('<div class="stats-badge">📊 247 Processed</div>', unsafe_allow_html=True)
+    with col2:
+        st.markdown('<div class="stats-badge">⚡ 2.3s Avg</div>', unsafe_allow_html=True)
+    
+    st.markdown("---")
+    st.markdown("### ✨ Features")
+    features = [
+        "📝 AI Summarization",
+        "💬 Smart Q&A",
+        "🎯 Quiz Generator",
+        "🌍 Multi-Language",
+        "🔑 Keyword Extraction",
+        "💨 Lightning Fast"
+    ]
+    for feat in features:
+        st.markdown(f"**{feat}**")
+    
+    st.markdown("---")
+    st.markdown("### 👩‍💻 Developer")
+    st.markdown("**Umaima Qureshi**")
+    st.markdown("[GitHub](https://github.com/Umaima122)")
+
+# Initialize session state
+for key in ["summary", "quiz", "translation", "keywords"]:
+    if key not in st.session_state:
+        st.session_state[key] = "" if key not in ["quiz", "keywords"] else []
+
+# Tabs
+tab1, tab2, tab3, tab4, tab5, tab6 = st.tabs([
+    "📝 Summarize", "💬 Q&A", "🎯 Quiz", "🌍 Translate", "🔑 Keywords", "📥 Download"
+])
+
+# ============================================
+# TAB 1: SUMMARIZE
+# ============================================
+with tab1:
+    st.markdown("### 📝 Intelligent Summarization")
+    
+    text = st.text_area(
+        "✍️ Your notes or textbook:", 
+        value="", 
+        height=250, 
+        key="sum_txt", 
+        placeholder="Paste your content here and watch AI magic happen..."
+    )
+    
+    col1, col2, col3 = st.columns([1, 1, 1])
+    with col2:
+        if st.button("✨ Generate Summary", key="sum_btn"):
+            if not text.strip():
+                st.error("⚠️ Please provide text to summarize")
+            else:
+                trunc, was_trunc = truncate_text(text, 400)
+                if was_trunc:
+                    st.info("📊 Text optimized to 400 words for processing")
+                
+                if len(trunc.split()) < 20:
+                    st.error("⚠️ Need at least 20 words to generate a meaningful summary")
+                else:
+                    with st.spinner("🧠 AI is thinking..."):
+                        try:
+                            summarizer = get_summarizer()
+                            if summarizer:
+                                result = summarizer(
+                                    trunc, 
+                                    max_length=130, 
+                                    min_length=30, 
+                                    do_sample=False
+                                )
+                                summary = result[0]['summary_text']
+                                
+                                st.markdown(f"""
+                                <div class="result-card">
+                                    <h4 style="color: #667eea; margin-bottom: 1rem;">📄 AI-Generated Summary</h4>
+                                    <p style="font-size: 1.1rem; line-height: 1.8; color: #2d3748;">{summary}</p>
+                                    <div style="margin-top: 1rem; padding-top: 1rem; border-top: 1px solid #e2e8f0;">
+                                        <span class="stats-badge" style="background: #667eea; color: white;">
+                                            {len(summary.split())} words
+                                        </span>
+                                        <span class="stats-badge" style="background: #48bb78; color: white;">
+                                            ✓ Completed
+                                        </span>
+                                    </div>
+                                </div>
+                                """, unsafe_allow_html=True)
+                                st.session_state["summary"] = summary
+                        except Exception as e:
+                            st.error(f"❌ Error generating summary: {str(e)}")
+
+# ============================================
+# TAB 2: Q&A
+# ============================================
+with tab2:
+    st.markdown("### 💬 Intelligent Q&A System")
+    
+    context = st.text_area(
+        "📚 Context (Your notes):", 
+        value="", 
+        height=200, 
+        key="qa_ctx",
+        placeholder="Paste your study material here..."
+    )
+    
+    question = st.text_input(
+        "❓ Ask your question:", 
+        key="qa_q",
+        placeholder="What would you like to know?"
+    )
+    
+    col1, col2, col3 = st.columns([1, 1, 1])
+    with col2:
+        if st.button("🔍 Get Answer", key="qa_btn"):
+            if not context.strip() or not question.strip():
+                st.error("⚠️ Please provide both context and question")
+            else:
+                trunc_ctx, _ = truncate_text(context, 400)
+                with st.spinner("🤔 Analyzing..."):
+                    try:
+                        qa_model = get_qa()
+                        if qa_model:
+                            result = qa_model(question=question, context=trunc_ctx)
+                            answer = result['answer']
+                            confidence = result.get('score', 0)
+                            
+                            st.markdown(f"""
+                            <div class="result-card">
+                                <h4 style="color: #667eea; margin-bottom: 1rem;">💡 AI Answer</h4>
+                                <p style="font-size: 1.2rem; line-height: 1.8; color: #2d3748; font-weight: 500;">{answer}</p>
+                                <div style="margin-top: 1rem; padding-top: 1rem; border-top: 1px solid #e2e8f0;">
+                                    <span class="stats-badge" style="background: #48bb78; color: white;">
+                                        ✓ Answer Found
+                                    </span>
+                                    <span class="stats-badge" style="background: #667eea; color: white;">
+                                        Confidence: {confidence:.1%}
+                                    </span>
+                                </div>
+                            </div>
+                            """, unsafe_allow_html=True)
+                    except Exception as e:
+                        st.error(f"❌ Error finding answer: {str(e)}")
+
+# ============================================
+# TAB 3: QUIZ - FIXED
+# ============================================
+with tab3:
+    st.markdown("### 🎯 AI Quiz Generator")
+    
+    quiz_ctx = st.text_area(
+        "📖 Study material:", 
+        value="", 
+        height=200, 
+        key="quiz_ctx",
+        placeholder="Paste content for quiz generation..."
+    )
+    
+    col1, col2, col3 = st.columns([1, 1, 1])
+    with col2:
+        if st.button("🚀 Generate Quiz", key="quiz_btn"):
+            if not quiz_ctx.strip():
+                st.error("⚠️ Please provide text for quiz generation")
+            else:
+                trunc_quiz, _ = truncate_text(quiz_ctx, 200)
+                with st.spinner("🎲 Creating questions..."):
+                    try:
+                        sentences = sent_tokenize(trunc_quiz)[:5]
+                        if len(sentences) == 0:
+                            st.warning("⚠️ Could not extract sentences from the text")
+                        else:
+                            questions = [f"What is the main concept in: '{s[:70]}...'?" for s in sentences if len(s) > 10]
+                            
+                            if questions:
+                                st.markdown('<div class="result-card">', unsafe_allow_html=True)
+                                st.markdown("<h4 style='color: #667eea;'>📝 Generated Quiz Questions</h4>", unsafe_allow_html=True)
+                                st.markdown('<div class="quiz-container">', unsafe_allow_html=True)
+                                for i, q in enumerate(questions, 1):
+                                    st.markdown(f"""
+                                    <div class='quiz-question-card'>
+                                        <strong>Question {i}:</strong> <span style='color: white;'>{q}</span>
+                                    </div>
+                                    """, unsafe_allow_html=True)
+                                st.markdown('</div></div>', unsafe_allow_html=True)
+                                st.session_state["quiz"] = questions
+                            else:
+                                st.warning("⚠️ Could not generate questions from the provided text")
+                    except Exception as e:
+                        st.error(f"❌ Error generating quiz: {str(e)}")
+
+# ============================================
+# TAB 4: TRANSLATE
+# ============================================
+with tab4:
+    st.markdown("### 🌍 AI Translation")
+    
+    trans_text = st.text_area(
+        "✍️ Text to translate:", 
+        height=200, 
+        key="trans_txt",
+        placeholder="Enter text to translate..."
+    )
+    
+    col1, col2 = st.columns(2)
+    with col1:
+        lang = st.selectbox(
+            "🎯 Target language:", 
+            ["French", "German", "Spanish", "Italian", "Hindi"]
+        )
+    
+    with col2:
+        st.write("")
+        st.write("")
+        if st.button("🌐 Translate Now", key="trans_btn"):
+            if not trans_text.strip():
+                st.error("⚠️ Please provide text to translate")
+            else:
+                model_map = {
+                    "French": "Helsinki-NLP/opus-mt-en-fr",
+                    "German": "Helsinki-NLP/opus-mt-en-de",
+                    "Spanish": "Helsinki-NLP/opus-mt-en-es",
+                    "Italian": "Helsinki-NLP/opus-mt-en-it",
+                    "Hindi": "Helsinki-NLP/opus-mt-en-hi"
+                }
+                
+                trunc_trans, _ = truncate_text(trans_text, 200)
+                with st.spinner(f"🌍 Translating to {lang}..."):
+                    try:
+                        translator = load_translator(model_map[lang])
+                        if translator:
+                            result = translator(trunc_trans, max_length=256)
+                            translation = result[0]['translation_text']
+                            
+                            st.markdown(f"""
+                            <div class="result-card">
+                                <h4 style="color: #667eea; margin-bottom: 1rem;">🌐 Translation ({lang})</h4>
+                                <p style="font-size: 1.2rem; line-height: 1.8; color: #2d3748;">{translation}</p>
+                                <div style="margin-top: 1rem; padding-top: 1rem; border-top: 1px solid #e2e8f0;">
+                                    <span class="stats-badge" style="background: #48bb78; color: white;">
+                                        ✓ Translated
+                                    </span>
+                                </div>
+                            </div>
+                            """, unsafe_allow_html=True)
+                            st.session_state["translation"] = translation
+                    except Exception as e:
+                        st.error(f"❌ Translation Error: {str(e)}")
+
+# ============================================
+# TAB 5: KEYWORDS - FIXED
+# ============================================
+with tab5:
+    st.markdown("### 🔑 AI Keyword Extraction")
+    
+    keyword_input = st.text_area(
+        "📝 Text for analysis:", 
+        value="", 
+        height=200, 
+        key="kw_txt",
+        placeholder="Paste text to extract key concepts..."
+    )
+    
+    col1, col2, col3 = st.columns([1, 1, 1])
+    with col2:
+        if st.button("🔍 Extract Keywords", key="kw_btn"):
+            if not keyword_input.strip():
+                st.error("⚠️ Please provide text for keyword extraction")
+            else:
+                trunc_kw, _ = truncate_text(keyword_input, 200)
+                with st.spinner("🔎 Analyzing concepts..."):
+                    try:
+                        classifier = get_classifier()
+                        if classifier:
+                            labels = ["technology", "science", "education", "health", "business", "finance", "medical", "engineering", "mathematics", "history"]
+                            result = classifier(trunc_kw, labels)
+                            keywords = [lbl for lbl, score in zip(result['labels'], result['scores']) if score > 0.3][:5]
+                            
+                            if keywords:
+                                st.markdown('<div class="result-card">', unsafe_allow_html=True)
+                                st.markdown("<h4 style='color: #667eea;'>🎯 Extracted Keywords</h4>", unsafe_allow_html=True)
+                                st.markdown('<div class="keywords-container">', unsafe_allow_html=True)
+                                kw_html = " ".join([
+                                    f"<span style='display: inline-block; background: linear-gradient(135deg, #667eea, #764ba2); color: white; padding: 12px 24px; border-radius: 25px; margin: 8px; font-size: 1rem; font-weight: 600; box-shadow: 0 4px 12px rgba(102, 126, 234, 0.3);'>{kw}</span>"
+                                    for kw in keywords
+                                ])
+                                st.markdown(kw_html, unsafe_allow_html=True)
+                                st.markdown('</div></div>', unsafe_allow_html=True)
+                                st.session_state["keywords"] = keywords
+                            else:
+                                st.info("ℹ️ No strong keywords found. Try providing more detailed text.")
+                    except Exception as e:
+                        st.error(f"❌ Error extracting keywords: {str(e)}")
+
+# ============================================
+# TAB 6: DOWNLOAD
+# ============================================
+with tab6:
+    st.markdown("### 📥 Download Results")
+    
+    def download_link(text, filename, emoji):
+        """Generate download link for text content"""
+        b64 = base64.b64encode(text.encode()).decode()
+        return f"""
+        <a href="data:file/txt;base64,{b64}" download="{filename}" 
+           style="display: inline-block; background: linear-gradient(135deg, #667eea, #764ba2); 
+           color: white; padding: 16px 32px; border-radius: 16px; text-decoration: none; 
+           font-weight: 700; font-size: 1.1rem; margin: 10px; box-shadow: 0 8px 24px rgba(102, 126, 234, 0.3);
+           transition: all 0.3s ease;">
+            {emoji} Download {filename}
+        </a>
+        """
+    
+    col1, col2 = st.columns(2)
+    
+    with col1:
+        if st.session_state["summary"]:
+            st.markdown(download_link(st.session_state["summary"], "summary.txt", "📄"), unsafe_allow_html=True)
+        else:
+            st.info("📄 Generate a summary first")
+            
+        if st.session_state["quiz"]:
+            quiz_text = "\n\n".join([f"Question {i}: {q}" for i, q in enumerate(st.session_state["quiz"], 1)])
+            st.markdown(download_link(quiz_text, "quiz.txt", "🎯"), unsafe_allow_html=True)
+        else:
+            st.info("🎯 Generate a quiz first")
+    
+    with col2:
+        if st.session_state["translation"]:
+            st.markdown(download_link(st.session_state["translation"], "translation.txt", "🌍"), unsafe_allow_html=True)
+        else:
+            st.info("🌍 Translate text first")
+            
+        if st.session_state["keywords"]:
+            keywords_text = "Extracted Keywords:\n\n" + "\n".join([f"- {kw}" for kw in st.session_state["keywords"]])
+            st.markdown(download_link(keywords_text, "keywords.txt", "🔑"), unsafe_allow_html=True)
+        else:
+            st.info("🔑 Extract keywords first")
+    
+    st.markdown("---")
+    
+    if not any([st.session_state["summary"], st.session_state["quiz"], 
+                st.session_state["translation"], st.session_state["keywords"]]):
+        st.warning("ℹ️ Generate content in other tabs to enable downloads")
+    else:
+        st.success("✅ Content ready for download! Click the buttons above.")
+
+# ============================================
+# PREMIUM FOOTER
+# ============================================
+st.markdown("""
+<div class="premium-footer">
+    <p style="font-size: 1.2rem; font-weight: 600;">
+        Built with ❤️ by 
+        <span style="background: linear-gradient(135deg, #ffffff, #e0e7ff); 
+                     -webkit-background-clip: text; 
+                     -webkit-text-fill-color: transparent; 
+                     font-weight: 700;">
+            Umaima Qureshi
+        </span>
+    </p>
+    <p style="font-size: 0.9rem;">© 2025 AI Study Helper Pro. All Rights Reserved.</p>
+    <p style="margin-top: 1rem;">
+        <a href="https://github.com/Umaima122" target="_blank" 
+           style="color: white; text-decoration: none; padding: 8px 20px; 
+                  background: rgba(255, 255, 255, 0.15); border-radius: 20px; 
+                  backdrop-filter: blur(10px); border: 1px solid rgba(255, 255, 255, 0.3);
+                  transition: all 0.3s ease; margin: 0 5px;">
+            🔗 GitHub
+        </a>
+        <a href="https://www.linkedin.com/in/umaima-qureshi" target="_blank" 
+           style="color: white; text-decoration: none; padding: 8px 20px; 
+                  background: rgba(255, 255, 255, 0.15); border-radius: 20px; 
+                  backdrop-filter: blur(10px); border: 1px solid rgba(255, 255, 255, 0.3);
+                  transition: all 0.3s ease; margin: 0 5px;">
+            💼 LinkedIn
+        </a>
+    </p>
+    <p style="font-size: 0.85rem; margin-top: 1rem; opacity: 0.8;">
+        Powered by Transformers • PyTorch • Streamlit • NLTK
+    </p>
+</div>
+""", unsafe_allow_html=True)