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Zero
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"""
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'''
<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}")
return "❌ Processing failed", f"Error: {str(e)}", '<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
) |