fix: S-tier prompt - hex to color name, blur UI text, remove watermarks

app/services/flux.py

@@ -6,6 +6,58 @@ import io
 from app.core.config import settings
 
 
+def hex_to_color_name(hex_color: str) -> str:
+    """Convert hex color to descriptive color name to prevent hex appearing in image."""
+    hex_color = hex_color.upper().replace('#', '')
+    
+    # Common brand colors mapping
+    color_map = {
+        '4285F4': 'vibrant blue',      # Google Blue
+        'DB4437': 'warm red',           # Google Red
+        'F4B400': 'golden yellow',      # Google Yellow
+        '0F9D58': 'fresh green',        # Google Green
+        '1877F2': 'facebook blue',
+        'FF0000': 'bold red',           # YouTube
+        '000000': 'deep black',
+        'FFFFFF': 'pure white',
+        '4A90D9': 'sky blue',
+        'FF6B6B': 'coral pink',
+        '6C5CE7': 'electric purple',
+        '00D4AA': 'mint green',
+        'FFD93D': 'sunny yellow',
+    }
+    
+    if hex_color in color_map:
+        return color_map[hex_color]
+    
+    # Parse RGB and describe
+    try:
+        r = int(hex_color[0:2], 16)
+        g = int(hex_color[2:4], 16)
+        b = int(hex_color[4:6], 16)
+        
+        # Determine dominant color
+        if r > g and r > b:
+            if r > 200: return 'bright red tones'
+            return 'warm red tones'
+        elif g > r and g > b:
+            if g > 200: return 'vibrant green tones'
+            return 'fresh green tones'
+        elif b > r and b > g:
+            if b > 200: return 'bright blue tones'
+            return 'cool blue tones'
+        elif r > 200 and g > 200:
+            return 'warm golden tones'
+        elif r > 200 and b > 200:
+            return 'magenta pink tones'
+        elif g > 200 and b > 200:
+            return 'cyan aqua tones'
+        else:
+            return 'neutral tones'
+    except:
+        return 'harmonious tones'
+
+
 async def generate_poster(analysis: dict) -> str:
     """
     Generate a poster using Flux.1-schnell based on analysis.
@@ -22,34 +74,34 @@ async def generate_poster(analysis: dict) -> str:
     """
     # Extract analysis data
     brand_name = analysis.get('brand_name', 'BRAND').upper()
-    business_type = analysis.get('business_type', 'Productivity')
     poster_objects = analysis.get('poster_objects', 'modern workspace elements')
     background_style = analysis.get('background_style', 'Clean gradient')
     primary_color = analysis.get('primary_color', '#4A90D9')
     mood = analysis.get('mood', 'Clean')
     
-    # === PROMPT MASTER'S TEXT GENERATION RULES FOR FLUX ===
+    # Convert hex to color name (prevents hex code appearing in image)
+    color_description = hex_to_color_name(primary_color)
+    
+    # === S-TIER PROMPT ENGINEER RULES ===
     # 
-    # Rule 1: Quote the text exactly - Flux reads quoted strings
-    # Rule 2: Specify font style and weight (bold, sans-serif, etc.)
-    # Rule 3: Specify exact position (top center, bottom left, etc.)
-    # Rule 4: Make text part of the design context (signage, neon, embossed)
-    # Rule 5: Keep text SHORT (1-2 words max for reliability)
+    # Rule 1: ONLY the brand name as readable text
+    # Rule 2: All other UI elements = blurred/abstract/no text
+    # Rule 3: Color as description, NOT hex code
+    # Rule 4: Explicit "no watermark" in both prompt and negative
+    # Rule 5: Clean, minimal composition
     
-    prompt = f"""High-end commercial poster design, vertical 9:16 format.
-
-Typography: Bold modern text "{brand_name}" prominently displayed at top center of the frame, clean sans-serif font, white text with subtle shadow, professional branding typography.
+    prompt = f"""Minimalist commercial poster, vertical 9:16 aspect ratio, ultra clean design.
 
-Scene: {poster_objects} arranged beautifully below the text, {background_style} setting, {mood.lower()} atmosphere.
+The word "{brand_name}" in bold white sans-serif typography, centered at top, professional lettering with soft drop shadow.
 
-Color palette: {primary_color} as accent color, harmonious tones throughout.
+Below: {poster_objects} with all screens and interfaces showing abstract colorful shapes and blurred gradients instead of text, no readable text on any UI element, purely visual design elements.
 
-Style: Premium advertising campaign aesthetic, Apple-style minimalism, magazine cover quality, professional product photography.
+Background: {background_style}, {mood.lower()} mood, {color_description} color scheme.
 
-Technical: Studio lighting, soft shadows, sharp focus, 8k resolution, commercial photography, masterpiece."""
+Style: Apple keynote presentation quality, premium advertising, high-end product showcase, pristine studio photography, no watermarks, no signatures, no logos except the brand name."""
     
-    # Negative prompt - allow text but block unwanted elements
-    negative_prompt = "blurry, noise, grainy, amateur, low quality, distorted, ugly, planets, space, galaxy, stars, cosmos, abstract art, random patterns, cluttered, messy, chaotic, bad typography, misspelled text, distorted letters, unreadable text"
+    # Aggressive negative prompt for clean output
+    negative_prompt = "watermark, signature, logo, copyright, trademark, website url, username, id number, serial number, code, hex code, random letters, gibberish text, corrupted text, glitched text, small text, fine print, label, tag, badge, stamp, readable text on screens, text on monitors, text on UI, multiple texts, extra text, any text except brand name"
     
     headers = {
         "Authorization": f"Bearer {settings.hf_token}",
@@ -61,15 +113,14 @@ Technical: Studio lighting, soft shadows, sharp focus, 8k resolution, commercial
         "inputs": prompt,
         "parameters": {
             "negative_prompt": negative_prompt,
-            "num_inference_steps": 4,  # Schnell is optimized for 4 steps
-            "guidance_scale": 0.0,     # Schnell uses guidance_scale 0
+            "num_inference_steps": 4,
+            "guidance_scale": 0.0,
             "width": 768,
             "height": 1344,
         }
     }
     
     async with httpx.AsyncClient(timeout=60.0) as client:
-        # Use new HF Router endpoint
         response = await client.post(
             f"https://router.huggingface.co/hf-inference/models/{settings.flux_model}",
             headers=headers,