A framework for prompt optimization and a zoo of prompt optimization algorithms
GeneticPromptLab uses genetic algorithms for automated prompt engineering (for LLMs), enhancing quality and diversity through iterative selection, crossover, and mutation, while efficiently exploring minimal yet diverse samples from the training set.
We introduce CAPO, a novel prompt optimization algorithm that integrates racing and multi-objective optimization for cost-efficiency and leverages few-shot examples and task descriptions, outperforming SOTA discrete prompt optimization methods.
A package for improving and evaluating LLM prompts
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