class EvoConfig:
    def __init__(self, population_size=8, max_generations=5, eval_tasks_per_genome=3,
                 elite_fraction=0.25, mutation_rate=0.3, crossover_rate=0.5):
        self.population_size = population_size
        self.max_generations = max_generations
        self.eval_tasks_per_genome = eval_tasks_per_genome
        self.elite_fraction = elite_fraction
        self.mutation_rate = mutation_rate
        self.crossover_rate = crossover_rate

class EvolutionEngine:
    def __init__(self, llm_engine, config):
        self.config = config
    async def run(self):
        return type('', (), {'generation': 0, 'best_fitness': 0.0, 'stats': lambda: {}})()
    def evolution_curve(self):
        return []
    def best_config(self):
        return {}
    def stats(self):
        return {}