""" 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__) # Initialize the optimizer globally optimizer = UltraSupremeOptimizer() def process_ultra_supreme_analysis(image): """Process image and generate ultra supreme analysis""" try: prompt, info, score, breakdown = optimizer.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'''
{score}
{grade_info["grade"]}
Ultra Supreme Intelligence Score
''' return prompt, info, score_html except Exception as e: logger.error(f"Ultra supreme wrapper error: {e}") return "❌ Processing failed", f"Error: {str(e)}", '
Error
' def clear_outputs(): """Clear all outputs and free memory""" gc.collect() if torch.cuda.is_available(): torch.cuda.empty_cache() return "", "", '
--
Ultra Supreme Score
' 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("""
🚀 ULTRA SUPREME FLUX OPTIMIZER
Maximum Absolute Intelligence • Triple CLIP Analysis • Zero Compromise • Research Supremacy
""") 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='
--
Ultra Supreme Score
' ) 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 )