import streamlit as st

# Custom CSS with modern design and animations
st.markdown("""
    <style>
    :root {
        --primary: #2E86C1;
        --secondary: #AED6F1;
        --accent: #FF6B6B;
    }
    
    body {
        background: linear-gradient(45deg, #f8f9fa, #e9ecef);
        font-family: 'Segoe UI', system-ui;
    }
    
    .title-box {
        background: linear-gradient(45deg, var(--primary), var(--secondary));
        padding: 2rem;
        border-radius: 15px;
        box-shadow: 0 4px 6px rgba(0,0,0,0.1);
        margin-bottom: 2rem;
    }
    
    h1 {
        color: white !important;
        font-family: 'Arial Rounded MT Bold';
        text-align: center;
        font-size: 2.5rem !important;
        text-shadow: 2px 2px 4px rgba(0,0,0,0.2);
    }
    
    .term-card {
        background: black;
        border-radius: 10px;
        padding: 1.5rem;
        margin: 1rem 0;
        box-shadow: 0 2px 4px rgba(0,0,0,0.05);
        transition: transform 0.2s;
        border-left: 4px solid var(--primary);
    }
    
    .term-card:hover {
        transform: translateY(-3px);
        box-shadow: 0 4px 6px rgba(0,0,0,0.1);
    }
    
    .custom-icon {
        font-size: 1.5rem;
        margin-right: 0.5rem;
    }
    
    .sidebar .sidebar-content {
        background: black !important;
        border-right: 2px solid var(--secondary);
    }
    
    .stExpander {
        border: none !important;
        box-shadow: none !important;
    }
    
    mark {
        background-color: var(--secondary);
        padding: 0.2em 0.4em;
        border-radius: 4px;
    }
    </style>
""", unsafe_allow_html=True)

# Sidebar with navigation
with st.sidebar:
    st.header("🔍 Navigation")
    page_section = st.radio("Jump to:", [
        "Basic Terms", 
        "Tokenization", 
        "Vectorization",
        "Advanced Concepts"
    ])

# Main content
st.markdown("""
    <div class='title-box'>
        <h1>📚 NLP Terminology Explorer</h1>
    </div>
""", unsafe_allow_html=True)

# Basic Terms Section
if page_section == "Basic Terms":
    st.markdown("### 🔍 Foundational Concepts")
    
    terms = [
        ("📚 Corpus", "A collection of documents"),
        ("📄 Document", "Collection of sentences, paragraphs, or text elements"),
        ("📝 Paragraph", "Multiple sentences forming a coherent block"),
        ("💬 Sentence", "Complete grammatical unit of words"),
        ("🔤 Word", "Basic unit of language with meaning"),
        ("🔠 Character", "Individual letters, numbers, or symbols")
    ]
    
    for term, definition in terms:
        with st.expander(term):
            st.markdown(f"""
                <div class='term-card'>
                    <p style='font-size: 1.1rem; color: white;'>{definition}</p>
                </div>
            """, unsafe_allow_html=True)

# Tokenization Section
elif page_section == "Tokenization":
    st.markdown("### ✂️ Text Segmentation Techniques")
    
    col1, col2 = st.columns([2, 3])
    
    with col1:
        st.markdown("""
            <div class='term-card'>
                <h4>What is Tokenization?</h4>
                <p>Process of breaking text into smaller meaningful units called tokens</p>
            </div>
        """, unsafe_allow_html=True)
        
    with col2:
        with st.expander("📐 Types of Tokenization"):
            st.markdown("""
                - **Sentence Tokenization** `(NLTK, spaCy)`  
                - **Word Tokenization** `(Treebank, Regex)`  
                - **Subword Tokenization** `(BPE, WordPiece)`  
                - **Character-level Tokenization**
            """)
            
    st.markdown("#### 🛠️ Tokenization Examples")
    tab1, tab2, tab3 = st.tabs(["Sentence", "Word", "Character"])
    
    with tab1:
        st.code("Text: 'Hello world! NLP is awesome.'\nSentences: ['Hello world!', 'NLP is awesome.']")
        
    with tab2:
        st.code("Sentence: 'I love NLP!'\nWords: ['I', 'love', 'NLP', '!']")
        
    with tab3:
        st.code("Word: 'Hello'\nCharacters: ['H', 'e', 'l', 'l', 'o']")

# Vectorization Section
elif page_section == "Vectorization":
    st.markdown("### 🔢 Text Representation Methods")
    
    techniques = {
        "Bag of Words": "Count-based representation ignoring word order",
        "TF-IDF": "Statistical measure of word importance",
        "Word2Vec": "Neural network-based word embeddings",
        "BERT": "Contextual embeddings using transformers"
    }
    
    for tech, desc in techniques.items():
        with st.expander(f"📊 {tech}"):
            st.markdown(f"""
                <div style='padding: 1rem; background: black; border-radius: 8px;'>
                    <p>{desc}</p>
                    <small>Example: {'...'}</small>
                </div>
            """, unsafe_allow_html=True)

# Advanced Concepts Section
elif page_section == "Advanced Concepts":
    st.markdown("### 🧠 Advanced NLP Concepts")
    
    concepts = [
        ("🚫 Stop Words", "Common words filtered during processing", 
         "the, is, at, which, on"),
        ("🏷️ POS Tagging", "Identifying grammatical components", 
         "Noun, Verb, Adjective"),
        ("📐 Dependency Parsing", "Analyzing grammatical structure",
         "Subject-verb relationships")
    ]
    
    for title, desc, examples in concepts:
        with st.expander(title):
            st.markdown(f"""
                <div class='term-card'>
                    <p><strong>{desc}</strong></p>
                    <div style='margin-top: 1rem; padding: 0.5rem; background: black; border-radius: 6px;'>
                        <small>Examples: {examples}</small>
                    </div>
                </div>
            """, unsafe_allow_html=True)

# Footer
st.markdown("---")
st.markdown("""
    <div style='text-align: center; color: #666; margin-top: 3rem;'>
        <p>🎓 Learn more about NLP with our interactive courses!</p>
        <button style='background: var(--primary); color: white; border: none; padding: 0.5rem 2rem; border-radius: 25px;'>
            Explore Courses
        </button>
    </div>
""", unsafe_allow_html=True)