app.py

"""
Ultra Supreme Flux Optimizer - Main Gradio Interface
"""

import gradio as gr
import torch
import gc
import logging
import warnings
import os

from optimizer import UltraSupremeOptimizer
from constants import SCORE_GRADES

# Configure warnings and environment
warnings.filterwarnings("ignore", category=FutureWarning)
warnings.filterwarnings("ignore", category=UserWarning)
os.environ["TOKENIZERS_PARALLELISM"] = "false"

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# NO inicializar el optimizer globalmente
optimizer = None


def get_optimizer():
    """Get or create optimizer instance"""
    global optimizer
    if optimizer is None:
        optimizer = UltraSupremeOptimizer()
    return optimizer


def process_ultra_supreme_analysis(image):
    """Process image and generate ultra supreme analysis"""
    try:
        # Obtener optimizer (lazy initialization)
        opt = get_optimizer()
        
        prompt, info, score, breakdown = opt.generate_ultra_supreme_prompt(image)
        
        # Find appropriate grade based on score
        grade_info = None
        for threshold, grade_data in sorted(SCORE_GRADES.items(), reverse=True):
            if score >= threshold:
                grade_info = grade_data
                break
        
        if not grade_info:
            grade_info = SCORE_GRADES[0]  # Default to lowest grade
            
        score_html = f'''
        <div style="text-align: center; padding: 2rem; background: linear-gradient(135deg, #f0fdf4 0%, #dcfce7 100%); border: 3px solid {grade_info["color"]}; border-radius: 16px; margin: 1rem 0; box-shadow: 0 8px 25px -5px rgba(0, 0, 0, 0.1);">
            <div style="font-size: 3rem; font-weight: 800; color: {grade_info["color"]}; margin: 0; text-shadow: 0 2px 4px rgba(0,0,0,0.1);">{score}</div>
            <div style="font-size: 1.25rem; color: #15803d; margin: 0.5rem 0; text-transform: uppercase; letter-spacing: 0.1em; font-weight: 700;">{grade_info["grade"]}</div>
            <div style="font-size: 1rem; color: #15803d; margin: 0; text-transform: uppercase; letter-spacing: 0.05em; font-weight: 500;">Ultra Supreme Intelligence Score</div>
        </div>
        '''
        
        return prompt, info, score_html
        
    except Exception as e:
        logger.error(f"Ultra supreme wrapper error: {e}", exc_info=True)
        error_msg = str(e)
        if "GPU" in error_msg:
            error_msg = "GPU processing failed. The system will automatically retry with CPU."
        return "❌ Processing failed", f"Error: {error_msg}", '<div style="text-align: center; color: red;">Error</div>'


def clear_outputs():
    """Clear all outputs and free memory"""
    gc.collect()
    if torch.cuda.is_available():
        torch.cuda.empty_cache()
    return "", "", '<div style="text-align: center; padding: 1rem;"><div style="font-size: 2rem; color: #ccc;">--</div><div style="font-size: 0.875rem; color: #999;">Ultra Supreme Score</div></div>'


def create_interface():
    """Create the Gradio interface"""
    
    css = """
    @import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700;800;900&display=swap');
    
    .gradio-container {
        max-width: 1600px !important;
        margin: 0 auto !important;
        font-family: 'Inter', -apple-system, BlinkMacSystemFont, sans-serif !important;
        background: linear-gradient(135deg, #f8fafc 0%, #f1f5f9 100%) !important;
    }
    
    /* FIX CRÍTICO PARA TEXTO BLANCO SOBRE BLANCO */
    .markdown-text, .markdown-text *, 
    .prose, .prose *,
    .gr-markdown, .gr-markdown *,
    div[class*="markdown"], div[class*="markdown"] * {
        color: #1f2937 !important;
    }
    
    .markdown-text h1, .markdown-text h2, .markdown-text h3, 
    .prose h1, .prose h2, .prose h3,
    .gr-markdown h1, .gr-markdown h2, .gr-markdown h3 {
        color: #111827 !important;
        font-weight: 700 !important;
    }
    
    .markdown-text p, .markdown-text li, .markdown-text ul, .markdown-text ol,
    .prose p, .prose li, .prose ul, .prose ol,
    .gr-markdown p, .gr-markdown li, .gr-markdown ul, .gr-markdown ol {
        color: #374151 !important;
    }
    
    .markdown-text strong, .prose strong, .gr-markdown strong {
        color: #111827 !important;
        font-weight: 700 !important;
    }
    
    /* Asegurar que las listas sean visibles */
    ul, ol {
        color: #374151 !important;
    }
    
    li {
        color: #374151 !important;
    }
    
    /* Bullets de listas */
    ul li::marker {
        color: #374151 !important;
    }
    
    .main-header {
        text-align: center;
        padding: 3rem 0 4rem 0;
        background: linear-gradient(135deg, #0c0a09 0%, #1c1917 30%, #292524 60%, #44403c 100%);
        color: white;
        margin: -2rem -2rem 3rem -2rem;
        border-radius: 0 0 32px 32px;
        box-shadow: 0 20px 50px -10px rgba(0, 0, 0, 0.25);
        position: relative;
        overflow: hidden;
    }
    
    .main-header::before {
        content: '';
        position: absolute;
        top: 0;
        left: 0;
        right: 0;
        bottom: 0;
        background: linear-gradient(45deg, rgba(59, 130, 246, 0.1) 0%, rgba(147, 51, 234, 0.1) 50%, rgba(236, 72, 153, 0.1) 100%);
        z-index: 1;
    }
    
    .main-title {
        font-size: 4rem !important;
        font-weight: 900 !important;
        margin: 0 0 1rem 0 !important;
        letter-spacing: -0.05em !important;
        background: linear-gradient(135deg, #60a5fa 0%, #3b82f6 25%, #8b5cf6 50%, #a855f7 75%, #ec4899 100%);
        -webkit-background-clip: text;
        -webkit-text-fill-color: transparent;
        background-clip: text;
        position: relative;
        z-index: 2;
    }
    
    .subtitle {
        font-size: 1.5rem !important;
        font-weight: 500 !important;
        opacity: 0.95 !important;
        margin: 0 !important;
        position: relative;
        z-index: 2;
        color: #ffffff !important;
    }
    
    .prompt-output {
        font-family: 'SF Mono', 'Monaco', 'Inconsolata', 'Roboto Mono', monospace !important;
        font-size: 15px !important;
        line-height: 1.8 !important;
        background: linear-gradient(135deg, #ffffff 0%, #f8fafc 100%) !important;
        border: 2px solid #e2e8f0 !important;
        border-radius: 20px !important;
        padding: 2.5rem !important;
        box-shadow: 0 20px 50px -10px rgba(0, 0, 0, 0.1) !important;
        transition: all 0.3s ease !important;
        color: #1f2937 !important;
    }
    
    .prompt-output:hover {
        box-shadow: 0 25px 60px -5px rgba(0, 0, 0, 0.15) !important;
        transform: translateY(-2px) !important;
    }
    
    /* Fix para el output de información */
    .gr-textbox label {
        color: #374151 !important;
    }
    
    /* Fix para footer */
    footer, .footer, [class*="footer"] {
        color: #374151 !important;
    }
    
    footer *, .footer *, [class*="footer"] * {
        color: #374151 !important;
    }
    
    footer a, .footer a, [class*="footer"] a {
        color: #3b82f6 !important;
        text-decoration: underline;
    }
    
    footer a:hover, .footer a:hover, [class*="footer"] a:hover {
        color: #2563eb !important;
    }
    
    /* Botones */
    .gr-button-primary {
        background: linear-gradient(135deg, #3b82f6 0%, #2563eb 100%) !important;
        border: none !important;
        color: white !important;
    }
    
    .gr-button-primary:hover {
        background: linear-gradient(135deg, #2563eb 0%, #1d4ed8 100%) !important;
        transform: translateY(-1px);
        box-shadow: 0 4px 12px rgba(37, 99, 235, 0.3);
    }
    
    /* Asegurar que TODOS los elementos de texto sean visibles */
    * {
        -webkit-text-fill-color: initial !important;
    }
    
    /* Solo el título principal mantiene su gradiente */
    .main-title {
        -webkit-text-fill-color: transparent !important;
    }
    """
    
    with gr.Blocks(
        theme=gr.themes.Soft(),
        title="🚀 Ultra Supreme Flux Optimizer",
        css=css
    ) as interface:
        
        gr.HTML("""
        <div class="main-header">
            <div class="main-title">🚀 ULTRA SUPREME FLUX OPTIMIZER</div>
            <div class="subtitle">Maximum Absolute Intelligence • Triple CLIP Analysis • Zero Compromise • Research Supremacy</div>
        </div>
        """)
        
        with gr.Row():
            with gr.Column(scale=1):
                gr.Markdown("## 🧠 Ultra Supreme Analysis Engine")
                
                image_input = gr.Image(
                    label="Upload image for MAXIMUM intelligence analysis",
                    type="pil",
                    height=500
                )
                
                analyze_btn = gr.Button(
                    "🚀 ULTRA SUPREME ANALYSIS",
                    variant="primary",
                    size="lg"
                )
                
                gr.Markdown("""
                ### 🔬 Maximum Absolute Intelligence
                
                **🚀 Triple CLIP Interrogation:**
                • Fast analysis for broad contextual mapping
                • Classic analysis for detailed feature extraction  
                • Best analysis for maximum depth intelligence
                
                **🧠 Ultra Deep Feature Extraction:**
                • Micro-age detection with confidence scoring
                • Cultural/religious context with semantic analysis
                • Facial micro-features and expression mapping
                • Emotional state and micro-expression detection
                • Environmental lighting and atmospheric analysis
                • Body language and pose interpretation
                • Technical photography optimization
                
                **⚡ Absolute Maximum Intelligence** - No configuration, no limits, no compromise.
                """)
            
            with gr.Column(scale=1):
                gr.Markdown("## ⚡ Ultra Supreme Result")
                
                prompt_output = gr.Textbox(
                    label="🚀 Ultra Supreme Optimized Flux Prompt",
                    placeholder="Upload an image to witness absolute maximum intelligence analysis...",
                    lines=12,
                    max_lines=20,
                    elem_classes=["prompt-output"],
                    show_copy_button=True
                )
                
                score_output = gr.HTML(
                    value='<div style="text-align: center; padding: 1rem;"><div style="font-size: 2rem; color: #ccc;">--</div><div style="font-size: 0.875rem; color: #999;">Ultra Supreme Score</div></div>'
                )
                
                info_output = gr.Markdown(value="")
                
                clear_btn = gr.Button("🗑️ Clear Ultra Analysis", size="sm")
        
        # Event handlers
        analyze_btn.click(
            fn=process_ultra_supreme_analysis,
            inputs=[image_input],
            outputs=[prompt_output, info_output, score_output]
        )
        
        clear_btn.click(
            fn=clear_outputs,
            outputs=[prompt_output, info_output, score_output]
        )
        
        gr.Markdown("""
        ---
        ### 🏆 Ultra Supreme Research Foundation
        
        This system represents the **absolute pinnacle** of image analysis and Flux prompt optimization. Using triple CLIP interrogation, 
        ultra-deep feature extraction, cultural context awareness, and emotional intelligence mapping, it achieves maximum possible 
        understanding and applies research-validated Flux rules with supreme intelligence.
        
        **🔬 Pariente AI Research Laboratory** • **🚀 Ultra Supreme Intelligence Engine**
        """)
    
    return interface


# Main execution
if __name__ == "__main__":
    demo = create_interface()
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=True,
        show_error=True
    )