Refactor concepts and update header branding

- Removed the "Review Stars Visual" entry from the concepts in data/concepts.py to streamline visual options.
- Updated the header component in Header.tsx to change the displayed text from "Creative Breakthrough" to "PsyAdGenesis" for consistent branding across the application.
- Enhanced the generator service in generator.py with improved import organization and optimized data retrieval methods for better performance.

data/concepts.py

@@ -116,7 +116,6 @@ CONCEPTS = {
         "name": "Social Proof",
         "concepts": [
             {"key": "testimonial_screenshot", "name": "Testimonial Screenshot", "structure": "Screenshot format", "visual": "Authentic testimonial"},
-            {"key": "review_stars", "name": "Review Stars Visual", "structure": "Stars dominate", "visual": "Large stars, rating"},
             {"key": "quote_card", "name": "Quote Card", "structure": "Quote as main visual", "visual": "Clear, readable"},
             {"key": "case_study_frame", "name": "Case Study Frame", "structure": "Case study format", "visual": "Results visible"},
             {"key": "crowd", "name": "Crowd Visual", "structure": "Many people visible", "visual": "Popular feel"},

frontend/components/layout/Header.tsx

@@ -35,7 +35,7 @@ export const Header: React.FC = () => {
                 <div className="absolute inset-0 bg-blue-500/20 rounded-full blur-xl group-hover:bg-cyan-500/20 transition-colors duration-300"></div>
               </div>
               <span className="text-2xl font-bold gradient-text group-hover:scale-105 transition-transform duration-300">
-                Creative Breakthrough
+                PsyAdGenesis
               </span>
             </Link>
           </div>

services/generator.py

@@ -5,33 +5,35 @@ Uses professional prompting techniques for PsyAdGenesis
 Saves ad creatives to Neon database with image URLs
 """
 
+# ============================================================================
+# IMPORTS
+# ============================================================================
+
+# Standard library
 import os
 import sys
-
-# Add parent directory to path for imports
-sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-
 import random
 import uuid
 import json
 import asyncio
 from datetime import datetime
 from typing import Dict, Any, List, Optional
-from concurrent.futures import ThreadPoolExecutor
 
+# Add parent directory to path for imports
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+# Local application imports
 from config import settings
 from services.llm import llm_service
 from services.image import image_service
 
-# Optional database import (for when asyncpg is available)
+# Optional service imports
 try:
     from services.database import db_service
 except ImportError:
-    # Database service not available (asyncpg not installed)
     db_service = None
     print("Note: Database service not available (asyncpg not installed). Ads will be generated but not saved to database.")
 
-# Optional R2 storage import
 try:
     from services.r2_storage import get_r2_storage
     r2_storage_available = True
@@ -39,7 +41,6 @@ except ImportError:
     r2_storage_available = False
     print("Note: R2 storage not available. Images will only be saved locally.")
 
-# Optional extensive import
 try:
     from services.third_flow import third_flow_service
     third_flow_available = True
@@ -47,6 +48,7 @@ except ImportError:
     third_flow_available = False
     print("Note: Extensive service not available.")
 
+# Data module imports
 from data import home_insurance, glp1
 from services.matrix import matrix_service
 from data.frameworks import get_frameworks_for_niche, get_framework_hook_examples, get_all_frameworks
@@ -61,6 +63,9 @@ from data.visuals import (
     get_random_composition, get_random_mood, get_color_palette, get_niche_visual_guidance
 )
 
+# ============================================================================
+# CONSTANTS
+# ============================================================================
 
 # Niche data loaders
 NICHE_DATA = {
@@ -68,10 +73,6 @@ NICHE_DATA = {
     "glp1": glp1.get_niche_data,
 }
 
-# Note: Frameworks are now loaded from data/frameworks.py
-# This provides comprehensive framework data with hooks, visual styles, and niche-specific recommendations
-
-
 # Age brackets for identity targeting (proven high-CTR pattern)
 AGE_BRACKETS = [
     {"label": "21-40", "color": "yellow/gold button"},
@@ -82,17 +83,7 @@ AGE_BRACKETS = [
     {"label": "70+ years old", "color": "gray box"},
 ]
 
-# Note: Prices are no longer hardcoded. The AI will decide contextually
-# whether to include prices and what specific amounts to use based on the ad format and strategy.
-
-# Note: Containers are now loaded from data/containers.py
-# This provides comprehensive container data with visual guidance, colors, fonts, and authenticity tips
-# Native containers (iMessage, WhatsApp, SMS, etc.) are preferred for ad-blindness bypass
-
-# Note: CAMERA_ANGLES, LIGHTING_STYLES, and COMPOSITIONS are now imported from data/visuals.py
-# This eliminates duplication and ensures consistency across the codebase
-
-# Old footage / vintage film styles
+# Vintage film visual styles
 VINTAGE_FILM_STYLES = [
     "grainy 8mm home movie footage from the 1970s, warm faded colors, light leaks",
     "old VHS tape recording with tracking lines, fuzzy edges, dated look",
@@ -126,10 +117,16 @@ class AdGenerator:
     Implements professional prompting techniques.
     """
     
+    # ========================================================================
+    # INITIALIZATION & UTILITY METHODS
+    # ========================================================================
+    
     def __init__(self):
         """Initialize the generator."""
         self.output_dir = settings.output_dir
         os.makedirs(self.output_dir, exist_ok=True)
+        # Cache niche data to avoid repeated function calls
+        self._niche_data_cache: Dict[str, Dict[str, Any]] = {}
     
     def _should_save_locally(self) -> bool:
         """
@@ -168,11 +165,22 @@ class AdGenerator:
             print(f"Warning: Failed to save image locally: {e}")
             return None
     
+    # ========================================================================
+    # DATA RETRIEVAL & CACHING METHODS
+    # ========================================================================
+    
     def _get_niche_data(self, niche: str) -> Dict[str, Any]:
-        """Load data for a specific niche."""
+        """Load data for a specific niche (cached for performance)."""
         if niche not in NICHE_DATA:
             raise ValueError(f"Unsupported niche: {niche}. Supported: {list(NICHE_DATA.keys())}")
-        return NICHE_DATA[niche]()
+        # Use cache to avoid repeated function calls
+        if niche not in self._niche_data_cache:
+            self._niche_data_cache[niche] = NICHE_DATA[niche]()
+        return self._niche_data_cache[niche]
+    
+    # ========================================================================
+    # STRATEGY & COMPATIBILITY METHODS
+    # ========================================================================
     
     def _get_framework_strategy_compatibility(self, framework_key: str, strategy_name: str) -> float:
         """
@@ -289,11 +297,14 @@ class AdGenerator:
         return [niche_data["strategies"][name] for name in strategy_names]
     
     def _random_hooks(self, strategies: List[Dict], count: int = 3) -> List[str]:
-        """Randomly select hooks from the chosen strategies."""
-        all_hooks = []
-        for strategy in strategies:
-            all_hooks.extend(strategy["hooks"])
-        return random.sample(all_hooks, min(count, len(all_hooks)))
+        """Randomly select hooks from the chosen strategies (optimized list building)."""
+        # Optimized: use list comprehension instead of extend in loop
+        all_hooks = [hook for strategy in strategies for hook in strategy["hooks"]]
+        return random.sample(all_hooks, min(count, len(all_hooks))) if all_hooks else []
+    
+    # ========================================================================
+    # VISUAL SELECTION METHODS
+    # ========================================================================
     
     def _get_visual_library_for_niche(self, niche: str) -> Dict[str, List[str]]:
         """
@@ -384,11 +395,9 @@ class AdGenerator:
                 if visuals:
                     selected_visuals.extend(random.sample(visuals, min(1, len(visuals))))
         
-        # If we need more, add random from any category
+        # If we need more, add random from any category (optimized: use list comprehension)
         if len(selected_visuals) < count:
-            all_visuals = []
-            for visuals in visual_library.values():
-                all_visuals.extend(visuals)
+            all_visuals = [v for visuals in visual_library.values() for v in visuals]
             remaining = count - len(selected_visuals)
             if all_visuals:
                 selected_visuals.extend(random.sample(all_visuals, min(remaining, len(all_visuals))))
@@ -408,28 +417,26 @@ class AdGenerator:
             niche: Niche name for visual library access
             use_library: Whether to use comprehensive visual library (improvement)
         """
-        all_styles = []
-        
+        # Optimized: use list comprehension instead of extend in loops
         # Get strategy-specific visuals
-        for strategy in strategies:
-            all_styles.extend(strategy.get("visual_styles", []))
+        all_styles = [style for strategy in strategies for style in strategy.get("visual_styles", [])]
         
         # Add visual library visuals (improvement)
         if use_library and niche:
-            for strategy in strategies:
-                library_visuals = self._select_visuals_from_library(niche, strategy.get("name", ""), count=1)
-                all_styles.extend(library_visuals)
-        
-        # Remove duplicates while preserving order
-        seen = set()
-        unique_styles = []
-        for style in all_styles:
-            if style not in seen:
-                seen.add(style)
-                unique_styles.append(style)
+            library_visuals = [
+                v for strategy in strategies 
+                for v in self._select_visuals_from_library(niche, strategy.get("name", ""), count=1)
+            ]
+            all_styles.extend(library_visuals)
         
+        # Remove duplicates while preserving order (optimized using dict.fromkeys)
+        unique_styles = list(dict.fromkeys(all_styles))
         return random.sample(unique_styles, min(count, len(unique_styles))) if unique_styles else []
     
+    # ========================================================================
+    # NICHE & CONTENT CONFIGURATION METHODS
+    # ========================================================================
+    
     def _get_niche_specific_guidance(self, niche: str) -> str:
         """Get niche-specific guidance for the prompt."""
         if niche == "home_insurance":
@@ -531,6 +538,10 @@ NICHE-SPECIFIC REQUIREMENTS (GLP-1 / WEIGHT LOSS):
         # Return compatible first, then others
         return compatible + [c for c in all_containers if c not in compatible]
     
+    # ========================================================================
+    # CONTAINER SELECTION METHODS
+    # ========================================================================
+    
     def _select_container(self, prefer_native: bool = True, strategy: str = "balanced", framework_key: Optional[str] = None) -> Dict[str, Any]:
         """
         Select a container type for native-looking ad format.
@@ -578,6 +589,10 @@ NICHE-SPECIFIC REQUIREMENTS (GLP-1 / WEIGHT LOSS):
         
         return container if container else get_random_container()
     
+    # ========================================================================
+    # PROMPT BUILDING METHODS
+    # ========================================================================
+    
     def _build_copy_prompt(
         self,
         niche: str,
@@ -1904,22 +1919,20 @@ CONCEPT: {concept['name']}
         if not researcher_output:
             raise ValueError("Researcher returned no results")
         
-        # Step 2: Retrieve knowledge (in parallel)
+        # Step 2: Retrieve knowledge (in parallel) - Optimized: use asyncio.to_thread instead of blocking .result()
         print("📚 Step 2: Retrieving marketing knowledge...")
-        from concurrent.futures import ThreadPoolExecutor
         
-        with ThreadPoolExecutor(max_workers=2) as executor:
-            book_future = executor.submit(
+        # Run synchronous operations in thread pool without blocking event loop
+        book_knowledge, ads_knowledge = await asyncio.gather(
+            asyncio.to_thread(
                 third_flow_service.retrieve_search,
                 target_audience, offer, niche_display
-            )
-            ads_future = executor.submit(
+            ),
+            asyncio.to_thread(
                 third_flow_service.retrieve_ads,
                 target_audience, offer, niche_display
             )
-            
-            book_knowledge = book_future.result()
-            ads_knowledge = ads_future.result()
+        )
         
         # Step 3: Creative Director
         print(f"🎨 Step 3: Creating {num_strategies} creative strategy/strategies...")
@@ -1941,22 +1954,19 @@ CONCEPT: {concept['name']}
         creative_strategies = creative_strategies[:num_strategies]
         print(f"📊 Using {len(creative_strategies)} strategy/strategies (requested: {num_strategies})")
         
-        # Step 4: Process strategies in parallel (designer + copywriter)
+        # Step 4: Process strategies in parallel (designer + copywriter) - Optimized: use asyncio.to_thread instead of ThreadPoolExecutor
         print(f"⚡ Step 4: Processing {len(creative_strategies)} strategies in parallel...")
-        from concurrent.futures import ThreadPoolExecutor as TPE
-        from functools import partial
-        
-        # Create a partial function that includes the niche parameter
-        process_strategy_with_niche = partial(
-            third_flow_service.process_strategy,
-            niche=niche_display
-        )
         
-        with TPE(max_workers=8) as executor:
-            strategy_results = list(executor.map(
-                process_strategy_with_niche,
-                creative_strategies
-            ))
+        # Process strategies concurrently using asyncio (non-blocking)
+        strategy_tasks = [
+            asyncio.to_thread(
+                third_flow_service.process_strategy,
+                strategy,
+                niche=niche_display
+            )
+            for strategy in creative_strategies
+        ]
+        strategy_results = await asyncio.gather(*strategy_tasks)
         
         # Step 5: Generate images for each strategy
         # Ensure we only process the requested number of strategies
@@ -2162,6 +2172,10 @@ CONCEPT: {concept['name']}
         else:
             raise ValueError("No ads generated from extensive")
     
+    # ========================================================================
+    # MATRIX-SPECIFIC PROMPT METHODS
+    # ========================================================================
+    
     def _build_matrix_ad_prompt(
         self,
         niche: str,