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import fal_client
from weave_prompt import TextToImageModel, ImageEvaluator, PromptRefiner
from PIL import Image
import numpy as np
from typing import Dict, Any
import os
from fal_image_generator import FalImageGenerator
class MockTextToImageModel(TextToImageModel):
"""Mock text-to-image model for demonstration."""
def __init__(self):
self.image_generator = FalImageGenerator()
def generate(self, prompt: str, **kwargs) -> Image.Image:
"""Generate an image using the fal image generator."""
return self.image_generator.generate_image(prompt, **kwargs)
class MockImageEvaluator(ImageEvaluator):
"""Mock image evaluator for demonstration."""
def generate_initial_prompt(self, target_img: Image.Image) -> str:
"""Generate a mock initial prompt."""
return "A beautiful image with vibrant colors"
def analyze_differences(self, generated_img: Image.Image, target_img: Image.Image) -> Dict[str, Any]:
"""Mock difference analysis."""
return {
"missing_elements": ["texture", "details"],
"style_differences": ["color intensity", "composition"]
}
class MockSimilarityMetric:
"""Mock similarity metric that gradually increases."""
def compute(self, generated_img: Image.Image, target_img: Image.Image) -> float:
"""Mock similarity computation that gradually increases."""
# Randomly increase similarity over time
return np.random.uniform(0.5, 0.95)
class MockPromptRefiner(PromptRefiner):
"""Mock prompt refiner for demonstration."""
def refine_prompt(self, current_prompt: str, analysis: Dict[str, Any], similarity_score: float) -> str:
"""Mock prompt refinement by adding random modifiers."""
modifiers = [
"with more detail",
"in vibrant colors",
"with better composition",
"high quality",
"masterfully crafted"
]
return f"{current_prompt}, {np.random.choice(modifiers)}" |