"""
🚀 Modern AI Assistant - Gradio 6 Application
A clean, professional interface showcasing modern Gradio 6 features.
"""

import gradio as gr
import time
import random
from datetime import datetime

# =============================================================================
# AI Assistant Functions
# =============================================================================

def generate_response(prompt: str, temperature: float, max_tokens: int) -> tuple:
    """Generate AI response with configurable parameters."""
    time.sleep(1)  # Simulate processing time
    responses = [
        "That's an interesting question! Let me think about it...",
        "I can help you with that. Based on my analysis...",
        "Great question! Here's what I found...",
        "Let me break that down for you...",
        "That's a complex topic, but I can provide some insights..."
    ]
    response = random.choice(responses)
    
    # Simulate token generation
    words = response.split()
    generated_words = []
    for i in range(min(len(words), max_tokens // 4)):
        generated_words.append(words[i])
        time.sleep(0.1)  # Simulate streaming effect
    
    final_response = " ".join(generated_words) + " " + random.choice([
        "How else can I assist you today?",
        "Is there anything else you'd like to know?",
        "Feel free to ask more questions!"
    ])
    
    return [[prompt, final_response]], ""

def analyze_sentiment(text: str) -> tuple[str, str]:
    """Analyze sentiment of the input text."""
    if not text.strip():
        return "Please enter text to analyze", ""
    
    positive_words = ["good", "great", "excellent", "amazing", "wonderful", "fantastic", "love", "like", "happy", "joy", "success"]
    negative_words = ["bad", "terrible", "awful", "hate", "dislike", "sad", "angry", "fail", "poor", "worst"]
    
    text_lower = text.lower()
    positive_count = sum(1 for word in positive_words if word in text_lower)
    negative_count = sum(1 for word in negative_words if word in text_lower)
    
    score = (positive_count - negative_count) / (len(text.split()) or 1)
    score = max(-1, min(1, score))  # Clamp between -1 and 1
    
    if score > 0.2:
        sentiment = "😊 Positive"
    elif score < -0.2:
        sentiment = "😟 Negative"
    else:
        sentiment = "😐 Neutral"
    
    result = f"{sentiment}\nScore: {round(score, 2)}"
    status = f"Analysis completed at {datetime.now().strftime('%H:%M:%S')}"
    
    return result, status

def translate_text(text: str, target_language: str) -> str:
    """Simulate text translation."""
    if not text.strip():
        return "Please enter text to translate"
    
    translations = {
        "English": "Hello! How can I help you today?",
        "Spanish": "¡Hola! ¿Cómo puedo ayudarte hoy?",
        "French": "Bonjour! Comment puis-je vous aider aujourd'hui?",
        "German": "Hallo! Wie kann ich Ihnen heute helfen?",
        "Japanese": "こんにちは！本日どのようにお手伝いできますか？",
        "Chinese": "你好！今天我能如何帮助你？"
    }
    
    base_translation = translations.get(target_language, f"Translation to {target_language}")
    return f"🌍 Translated to {target_language}:\n\n{base_translation}\n\n(Simulated translation of: '{text[:50]}...')"

def analyze_documents(files) -> tuple[str, str]:
    """Analyze uploaded documents."""
    if not files:
        return "No files uploaded", ""
    
    file_count = len(files) if isinstance(files, list) else 1
    result = f"📊 Analyzed {file_count} document{'s' if file_count > 1 else ''}.\n\n"
    result += "✅ Processing complete!\n"
    result += "• Extracted text content\n"
    result += "• Analyzed document structure\n"
    result += "• Generated metadata\n"
    
    status = f"📅 Analysis completed at {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
    
    return result, status

def clear_all():
    """Clear all fields."""
    return None, "", "", "", "", ""

# =============================================================================
# Gradio 6 Interface
# =============================================================================

def create_modern_interface() -> gr.Blocks:
    """Create a modern, professional Gradio 6 interface."""
    
    # Define custom theme
    theme = gr.themes.Soft(
        primary_hue="blue",
        secondary_hue="indigo",
        neutral_hue="slate",
        font=gr.themes.GoogleFont("Inter"),
        text_size="lg",
        spacing_size="lg",
        radius_size="md"
    ).set(
        button_primary_background_fill="*primary_600",
        button_primary_background_fill_hover="*primary_700",
        button_primary_text_color="white",
        block_title_text_weight="600",
        block_label_text_weight="500",
        input_border_color="*neutral_300",
        input_focus_border_color="*primary_500",
        slider_active_color="*primary_500",
        slider_color="*neutral_300"
    )
    
    # Custom CSS
    custom_css = """
    /* Modern Design System */
    .gradio-container {
        max-width: 1200px !important;
        margin: 0 auto !important;
        padding: 2rem !important;
        font-family: 'Inter', sans-serif !important;
    }
    
    /* Header Styling */
    .header-text h1 {
        font-size: 2.5rem !important;
        font-weight: 700 !important;
        margin-bottom: 1rem !important;
        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
        -webkit-background-clip: text;
        -webkit-text-fill-color: transparent;
        background-clip: text;
    }
    
    .header-text p {
        font-size: 1.2rem !important;
        color: #64748b !important;
        line-height: 1.6 !important;
    }
    
    /* Chat Container */
    .chat-container {
        border: 1px solid #e2e8f0 !important;
        border-radius: 12px !important;
        background: #ffffff !important;
        box-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.1) !important;
    }
    
    /* Message Input */
    .message-input textarea {
        border-radius: 8px !important;
        border: 2px solid #e2e8f0 !important;
        font-size: 1rem !important;
        padding: 0.75rem 1rem !important;
        transition: all 0.3s ease !important;
    }
    
    .message-input textarea:focus {
        border-color: #667eea !important;
        box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.1) !important;
    }
    
    /* Buttons */
    .send-button {
        font-size: 1.1rem !important;
        padding: 0.75rem 2rem !important;
        border-radius: 8px !important;
        font-weight: 600 !important;
        box-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.1) !important;
        transition: all 0.3s ease !important;
    }
    
    .send-button:hover {
        transform: translateY(-2px) !important;
        box-shadow: 0 10px 15px -3px rgb(0 0 0 / 0.2) !important;
    }
    
    /* File Upload Area */
    .file-upload-area {
        border: 2px dashed #cbd5e1 !important;
        border-radius: 12px !important;
        transition: all 0.3s ease !important;
        padding: 1rem !important;
    }
    
    .file-upload-area:hover {
        border-color: #667eea !important;
        background: #f8fafc !important;
    }
    
    /* Mobile Responsiveness */
    @media (max-width: 768px) {
        .gradio-container {
            padding: 1rem !important;
        }
        
        .header-text h1 {
            font-size: 2rem !important;
        }
    }
    """
    
    with gr.Blocks(theme=theme, css=custom_css) as demo:
        # Header with branding
        with gr.Row():
            with gr.Column(scale=1):
                gr.Markdown(
                    """
                    # 🤖 Modern AI Assistant
                    
                    Experience the power of AI with our advanced language models. 
                    Built with cutting-edge technology for seamless interactions.
                    """,
                    elem_classes=["header-text"]
                )
        
        gr.Markdown("---")
        
        # Main Content Area
        with gr.Row():
            with gr.Column(scale=1):
                # Chat Interface
                chatbot = gr.Chatbot(
                    height=400,
                    label="🗨️ AI Conversation",
                    elem_classes=["chat-container"]
                )
                
                # Input Section
                with gr.Row():
                    user_input = gr.Textbox(
                        placeholder="Type your message here...",
                        label="Your Message",
                        elem_classes=["message-input"],
                        lines=2
                    )
                    send_btn = gr.Button(
                        "➤ Send",
                        variant="primary",
                        elem_classes=["send-button"]
                    )
                
                # Generation Controls
                with gr.Row():
                    with gr.Column(scale=2):
                        temperature = gr.Slider(
                            minimum=0.1,
                            maximum=1.0,
                            value=0.7,
                            step=0.1,
                            label="🔥 Temperature",
                            info="Controls randomness (0.1=precise, 1.0=creative)"
                        )
                    with gr.Column(scale=2):
                        max_tokens = gr.Slider(
                            minimum=10,
                            maximum=200,
                            value=50,
                            step=10,
                            label="📝 Max Tokens",
                            info="Maximum response length"
                        )
                
                # Additional Features
                with gr.Accordion("🔧 Advanced Features", open=False):
                    with gr.Row():
                        with gr.Column(scale=1):
                            sentiment_btn = gr.Button("📊 Analyze Sentiment")
                            sentiment_output = gr.Textbox(
                                label="Sentiment Analysis",
                                interactive=False,
                                lines=3
                            )
                        with gr.Column(scale=1):
                            translate_btn = gr.Button("🌍 Translate")
                            language_dropdown = gr.Dropdown(
                                choices=["English", "Spanish", "French", "German", "Japanese", "Chinese"],
                                value="Spanish",
                                label="Target Language"
                            )
                            translation_output = gr.Textbox(
                                label="Translation",
                                interactive=False,
                                lines=3
                            )
                
                # File Upload for Document Analysis
                with gr.Row():
                    file_upload = gr.File(
                        file_count="multiple",
                        file_types=[".pdf", ".txt", ".docx"],
                        label="📄 Upload Documents",
                        elem_classes=["file-upload-area"]
                    )
                
                with gr.Row():
                    analyze_btn = gr.Button(
                        "🔍 Analyze Documents",
                        variant="secondary"
                    )
                    clear_btn = gr.Button(
                        "🗑️ Clear All",
                        variant="stop"
                    )
                
                analysis_output = gr.Textbox(
                    label="Document Analysis",
                    interactive=False,
                    lines=6
                )
        
        # Status Section
        gr.Markdown("---")
        with gr.Row():
            status_output = gr.Textbox(
                label="📊 Status",
                interactive=False,
                lines=2
            )
        
        # Event Handlers - CORRIGIDO: Removido api_visibility
        send_btn.click(
            fn=generate_response,
            inputs=[user_input, temperature, max_tokens],
            outputs=[chatbot, user_input],
            api_name="generate"
        )
        
        user_input.submit(
            fn=generate_response,
            inputs=[user_input, temperature, max_tokens],
            outputs=[chatbot, user_input],
            api_name="generate_submit"
        )
        
        sentiment_btn.click(
            fn=analyze_sentiment,
            inputs=[user_input],
            outputs=[sentiment_output, status_output],
            api_name="sentiment"
        )
        
        translate_btn.click(
            fn=translate_text,
            inputs=[user_input, language_dropdown],
            outputs=[translation_output],
            api_name="translate"
        )
        
        analyze_btn.click(
            fn=analyze_documents,
            inputs=[file_upload],
            outputs=[analysis_output, status_output],
            api_name="analyze_docs"
        )
        
        clear_btn.click(
            fn=clear_all,
            inputs=[],
            outputs=[chatbot, user_input, sentiment_output, translation_output, analysis_output, status_output],
            api_name=False
        )
    
    return demo

# =============================================================================
# MAIN EXECUTION
# =============================================================================

if __name__ == "__main__":
    # Create the interface
    demo = create_modern_interface()
    
    # Launch with modern Gradio 6 configuration
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False,
        max_file_size="100mb",
        show_error=True
    )