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Drift Johnson
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"""
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Batch Processing Script for Image Prompt Variations
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Automates generation of multiple prompt variations from input templates
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"""
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import json
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from pathlib import Path
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from typing import List, Dict, Optional
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from prompt_orchestrator import PromptOrchestrator, ModifierCategory
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class BatchProcessor:
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"""Handles batch processing of image prompts with various automation features"""
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def __init__(self, output_dir: str = "output"):
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"""
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Initialize batch processor.
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Args:
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output_dir: Directory to save output files
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"""
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self.orchestrator = PromptOrchestrator()
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self.output_dir = Path(output_dir)
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self.output_dir.mkdir(exist_ok=True)
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def process_single_prompt(self, base_prompt: str, config: Dict) -> List[Dict]:
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"""
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Process a single prompt with specified configuration.
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Args:
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base_prompt: The base prompt to vary
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config: Configuration dict with keys:
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- lighting_ids: List of modifier IDs (or "all", "dry", "wet")
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- styles: List of style names to apply
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- export_format: Output format (txt, json, csv)
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Returns:
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List of variation dictionaries
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"""
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# Determine which lighting modifiers to use
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if config.get("lighting_ids") == "all":
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modifier_ids = list(range(1, 21))
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elif config.get("lighting_ids") == "dry":
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dry_mods = self.orchestrator.get_modifiers_by_category(ModifierCategory.DRY)
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modifier_ids = [m.id for m in dry_mods]
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elif config.get("lighting_ids") == "wet":
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wet_mods = self.orchestrator.get_modifiers_by_category(ModifierCategory.WET)
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modifier_ids = [m.id for m in wet_mods]
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else:
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modifier_ids = config.get("lighting_ids", [])
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# Generate variations
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variations = self.orchestrator.generate_variation_batch(
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base_prompt=base_prompt,
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modifier_ids=modifier_ids if modifier_ids else None,
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include_styles=config.get("styles", None)
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)
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return variations
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def process_multiple_prompts(self, prompts: List[str], config: Dict,
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output_filename: str = "batch_output") -> str:
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"""
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Process multiple base prompts and save results.
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Args:
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prompts: List of base prompts
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config: Configuration dictionary
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output_filename: Name for output file (without extension)
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Returns:
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Path to output file
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"""
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all_results = []
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for idx, prompt in enumerate(prompts, 1):
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variations = self.process_single_prompt(prompt, config)
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all_results.append({
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"base_prompt_id": idx,
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"base_prompt": prompt,
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"variations": variations
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})
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# Export results
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export_format = config.get("export_format", "json")
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output_path = self.output_dir / f"{output_filename}.{export_format}"
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if export_format == "json":
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with open(output_path, "w", encoding="utf-8") as f:
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json.dump(all_results, f, indent=2)
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elif export_format == "txt":
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with open(output_path, "w", encoding="utf-8") as f:
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for result in all_results:
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f.write(f"\n{'=' * 80}\n")
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f.write(f"BASE PROMPT #{result['base_prompt_id']}: {result['base_prompt']}\n")
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f.write(f"{'=' * 80}\n\n")
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for var in result['variations']:
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f.write(f"[{var['id']}] {var['type'].upper()} - {var['category']}\n")
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f.write(f" Description: {var['description']}\n")
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f.write(f" Prompt: {var['prompt']}\n\n")
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elif export_format == "csv":
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with open(output_path, "w", encoding="utf-8") as f:
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f.write("base_prompt_id,base_prompt,variation_id,type,category,description,prompt\n")
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for result in all_results:
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for var in result['variations']:
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f.write(f"{result['base_prompt_id']},\"{result['base_prompt']}\",")
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f.write(f"{var['id']},{var['type']},{var['category']},")
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f.write(f"\"{var['description']}\",\"{var['prompt']}\"\n")
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return str(output_path)
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def create_preset_collection(self, base_prompt: str, preset: str) -> List[Dict]:
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"""
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Apply a preset collection of variations.
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Presets:
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- "full_day_cycle": All DRY modifiers (complete day cycle)
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- "wet_night": All WET modifiers (dramatic night scenes)
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- "key_moments": Selected dramatic lighting moments
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- "commercial": Best modifiers for commercial photography
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Args:
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base_prompt: The base prompt
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preset: Preset name
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Returns:
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List of variations
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"""
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preset_configs = {
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"full_day_cycle": {
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"lighting_ids": "dry",
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"styles": None
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},
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"wet_night": {
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"lighting_ids": "wet",
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"styles": None
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},
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"key_moments": {
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"lighting_ids": [1, 7, 8, 10, 18, 20], # Sunrise, golden hour, sunset, blue hours, wet night
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"styles": None
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},
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"commercial": {
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"lighting_ids": [3, 4, 7, 11], # Crisp lighting for product shots
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"styles": None
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},
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"artistic": {
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"lighting_ids": [7, 8, 9, 10],
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"styles": ["impressionist", "minimalist", "art_deco"]
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}
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}
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if preset not in preset_configs:
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raise ValueError(f"Unknown preset: {preset}. Available: {list(preset_configs.keys())}")
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return self.process_single_prompt(base_prompt, preset_configs[preset])
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def generate_comparison_set(self, base_prompt: str,
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modifier_pairs: List[tuple]) -> List[Dict]:
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"""
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Generate side-by-side comparison prompts.
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Args:
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base_prompt: Base prompt
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modifier_pairs: List of (modifier_id_1, modifier_id_2) tuples
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Returns:
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List of comparison variation sets
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"""
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comparisons = []
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for mod_a, mod_b in modifier_pairs:
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prompt_a = self.orchestrator.apply_lighting_modifier(base_prompt, mod_a)
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prompt_b = self.orchestrator.apply_lighting_modifier(base_prompt, mod_b)
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comparisons.append({
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"comparison_type": f"modifier_{mod_a}_vs_{mod_b}",
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"variant_a": {
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"modifier_id": mod_a,
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"description": self.orchestrator.modifiers[mod_a].description,
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"prompt": prompt_a
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},
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"variant_b": {
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"modifier_id": mod_b,
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"description": self.orchestrator.modifiers[mod_b].description,
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"prompt": prompt_b
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}
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})
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return comparisons
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def example_workflows():
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"""Demonstrate various workflow scenarios"""
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processor = BatchProcessor(output_dir="prompt_variations")
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print("BATCH PROCESSING WORKFLOWS\n")
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print("=" * 80)
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# Workflow 1: Single prompt with all lighting variations
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print("\n1. FULL LIGHTING CYCLE GENERATION")
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print("-" * 80)
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base_prompt_1 = "Luxury sedan in urban environment, architectural background"
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config_full = {
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"lighting_ids": "all",
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"export_format": "json"
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}
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output_1 = processor.process_multiple_prompts(
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prompts=[base_prompt_1],
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config=config_full,
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output_filename="full_lighting_cycle"
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)
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print(f"✓ Generated full lighting cycle → {output_1}")
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# Workflow 2: Multiple prompts with preset
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print("\n2. KEY MOMENTS PRESET (Multiple Prompts)")
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print("-" * 80)
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base_prompts = [
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"Sports car on mountain road, scenic vista",
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"Classic convertible on beach, sunset backdrop",
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"Electric SUV in modern city, glass buildings"
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]
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variations = []
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for prompt in base_prompts:
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vars = processor.create_preset_collection(prompt, "key_moments")
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variations.extend(vars)
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print(f"✓ Generated {len(variations)} variations across {len(base_prompts)} base prompts")
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# Workflow 3: Style transformations
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print("\n3. STYLE TRANSFORMATION SET")
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print("-" * 80)
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base_prompt_3 = "Vintage motorcycle in garage, mechanical details"
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config_styles = {
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"lighting_ids": [7], # Golden hour only
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"styles": ["cyberpunk", "art_deco", "minimalist", "noir"],
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"export_format": "txt"
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}
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output_3 = processor.process_multiple_prompts(
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prompts=[base_prompt_3],
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config=config_styles,
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output_filename="style_variations"
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)
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print(f"✓ Generated style variations → {output_3}")
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# Workflow 4: Comparison set
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print("\n4. COMPARISON SET GENERATION")
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print("-" * 80)
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base_prompt_4 = "Modern architecture, geometric forms"
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comparison_pairs = [
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(4, 7), # Midday vs Golden Hour
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(11, 18), # Night dry vs Night wet
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(1, 8) # Sunrise vs Sunset
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]
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comparisons = processor.generate_comparison_set(base_prompt_4, comparison_pairs)
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# Save comparisons
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output_4 = processor.output_dir / "comparisons.json"
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with open(output_4, "w", encoding="utf-8") as f:
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json.dump(comparisons, f, indent=2)
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print(f"✓ Generated {len(comparisons)} comparison sets → {output_4}")
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# Workflow 5: Commercial photography set
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print("\n5. COMMERCIAL PHOTOGRAPHY PRESET")
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print("-" * 80)
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base_prompt_5 = "Product shot of smartwatch, clean background"
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commercial_vars = processor.create_preset_collection(base_prompt_5, "commercial")
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print(f"✓ Generated {len(commercial_vars)} commercial-grade variations")
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print("\n" + "=" * 80)
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print("All workflows completed successfully!")
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print(f"Output directory: {processor.output_dir}")
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def quick_generation_example():
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"""Quick example for immediate use"""
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orchestrator = PromptOrchestrator()
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# Your base prompt
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base = "Ferrari on coastal highway at sunset"
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print("\nQUICK GENERATION EXAMPLES")
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print("=" * 80)
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# Generate 5 quick variations
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variations = [
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orchestrator.apply_lighting_modifier(base, 1), # Sunrise
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orchestrator.apply_lighting_modifier(base, 7), # Golden hour
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orchestrator.apply_lighting_modifier(base, 10), # Blue hour
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orchestrator.apply_lighting_modifier(base, 18), # Blue hour wet
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orchestrator.apply_style_transformation(base, "cyberpunk")
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]
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for i, var in enumerate(variations, 1):
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print(f"\n{i}. {var}")
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if __name__ == "__main__":
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# Run example workflows
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example_workflows()
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# Quick generation
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quick_generation_example()
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