app.py

import gradio as gr
import re

# Mock detection logic (replace with your actual model)
def detect_ai_human(text):
    if not text.strip():
        return "⚠️ Please enter some text to analyze."
    
    # Simple demo logic — replace with your 90.5% accuracy model
    ai_indicators = ["additionally", "furthermore", "moreover", "in conclusion", 
                     "it is important to note", "on the other hand"]
    score = sum(1 for word in ai_indicators if word in text.lower())
    ai_prob = min(95, score * 15 + 10)
    human_prob = 100 - ai_prob
    
    if ai_prob > 60:
        verdict = "🤖 AI-Generated"
        color = "#f43f5e"
    else:
        verdict = "👤 Human-Written"
        color = "#10b981"
    
    return f"""
    <div style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); border-radius: 20px; padding: 25px; color: white;">
        <h2 style="margin: 0 0 15px 0;">📊 Analysis Result</h2>
        <div style="background: rgba(255,255,255,0.15); border-radius: 15px; padding: 20px;">
            <div style="font-size: 48px; font-weight: bold; margin-bottom: 10px;">{verdict}</div>
            <div style="display: flex; gap: 20px; margin-top: 20px;">
                <div style="flex: 1; text-align: center;">
                    <div style="font-size: 14px; opacity: 0.9;">AI Probability</div>
                    <div style="font-size: 36px; font-weight: bold;">{ai_prob:.1f}%</div>
                </div>
                <div style="flex: 1; text-align: center;">
                    <div style="font-size: 14px; opacity: 0.9;">Human Probability</div>
                    <div style="font-size: 36px; font-weight: bold;">{human_prob:.1f}%</div>
                </div>
            </div>
        </div>
    </div>
    """

# Custom CSS for modern, beautiful UI
custom_css = """
* {
    margin: 0;
    padding: 0;
    box-sizing: border-box;
}

body {
    background: linear-gradient(135deg, #0f0c29, #302b63, #24243e);
    min-height: 100vh;
}

.gradio-container {
    max-width: 1000px !important;
    margin: 0 auto !important;
    padding: 40px 20px !important;
    background: transparent !important;
}

.main-header {
    text-align: center;
    margin-bottom: 40px;
}

.main-header h1 {
    font-size: 3rem;
    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
    -webkit-background-clip: text;
    -webkit-text-fill-color: transparent;
    background-clip: text;
    margin-bottom: 15px;
    font-weight: 800;
}

.main-header p {
    color: #a0a0b0;
    font-size: 1.1rem;
}

.feature-badge {
    display: inline-flex;
    gap: 15px;
    justify-content: center;
    margin-top: 20px;
    flex-wrap: wrap;
}

.badge {
    background: rgba(102, 126, 234, 0.15);
    backdrop-filter: blur(10px);
    padding: 8px 16px;
    border-radius: 40px;
    font-size: 0.85rem;
    color: #a0a0ff;
    border: 1px solid rgba(102, 126, 234, 0.3);
}

.input-card {
    background: rgba(30, 30, 50, 0.6);
    backdrop-filter: blur(10px);
    border-radius: 24px;
    padding: 30px;
    border: 1px solid rgba(255, 255, 255, 0.1);
    margin-bottom: 25px;
}

label {
    color: #e0e0ff !important;
    font-weight: 600 !important;
    font-size: 1rem !important;
    margin-bottom: 12px !important;
}

textarea {
    background: rgba(20, 20, 35, 0.8) !important;
    border: 1px solid rgba(102, 126, 234, 0.3) !important;
    border-radius: 16px !important;
    color: white !important;
    font-size: 1rem !important;
    padding: 16px !important;
    transition: all 0.3s ease !important;
}

textarea:focus {
    border-color: #667eea !important;
    box-shadow: 0 0 20px rgba(102, 126, 234, 0.2) !important;
    outline: none !important;
}

button {
    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
    border: none !important;
    border-radius: 40px !important;
    padding: 12px 32px !important;
    font-weight: 600 !important;
    font-size: 1rem !important;
    color: white !important;
    transition: all 0.3s ease !important;
    cursor: pointer !important;
}

button:hover {
    transform: translateY(-2px);
    box-shadow: 0 10px 25px rgba(102, 126, 234, 0.3);
}

#clear_btn {
    background: rgba(255, 255, 255, 0.1) !important;
    backdrop-filter: blur(10px);
}

#clear_btn:hover {
    background: rgba(255, 255, 255, 0.2) !important;
    transform: translateY(-2px);
}

.output-area {
    background: rgba(30, 30, 50, 0.6);
    backdrop-filter: blur(10px);
    border-radius: 24px;
    padding: 5px;
    border: 1px solid rgba(255, 255, 255, 0.1);
}

.footer {
    text-align: center;
    margin-top: 40px;
    padding-top: 20px;
    border-top: 1px solid rgba(255, 255, 255, 0.1);
    color: #707080;
    font-size: 0.85rem;
}
"""

# Build the app
with gr.Blocks(css=custom_css, title="AI vs Human Text Detector") as demo:
    # Header
    gr.HTML("""
    <div class="main-header">
        <h1>🔍 AI vs Human Text Detector</h1>
        <p>Advanced detection with 90.5% accuracy — Identify AI-generated content instantly</p>
        <div class="feature-badge">
            <span class="badge">🎯 90.5% Accuracy</span>
            <span class="badge">💻 Code Detection</span>
            <span class="badge">📝 Sentence Analysis</span>
            <span class="badge">⚡ Real-time Results</span>
        </div>
    </div>
    """)
    
    # Main input card
    with gr.Column(elem_classes=["input-card"]):
        text_input = gr.Textbox(
            label="📝 Enter your text",
            placeholder="Paste or type text here... (e.g., essays, articles, code, emails)",
            lines=10,
            show_label=True
        )
        
        with gr.Row():
            clear_btn = gr.Button("🗑️ Clear", elem_id="clear_btn", scale=1)
            submit_btn = gr.Button("🚀 Analyze Text", variant="primary", scale=2)
    
    # Output section
    with gr.Column(elem_classes=["output-area"]):
        output_html = gr.HTML(label="")
    
    # Footer
    gr.HTML("""
    <div class="footer">
        <p>⚡ Detects ChatGPT, GPT-4, Claude, Gemini, and other LLMs • Sentence-level confidence scoring</p>
    </div>
    """)
    
    # Wire up buttons
    submit_btn.click(
        fn=detect_ai_human,
        inputs=text_input,
        outputs=output_html
    )
    
    clear_btn.click(
        fn=lambda: ("", ""),
        inputs=[],
        outputs=[text_input, output_html]
    )

if __name__ == "__main__":
    demo.launch()