Prompt optimization has become crucial for enhancing the performance of large language models (LLMs) across a broad range of tasks. Although many research papers show its effectiveness, practical adoption is hindered as existing implementations are often tied to unmaintained and isolated research codebases. To address this, we introduce promptolution, a unified and modular open-source framework that provides all components required for prompt optimization within a single extensible system for both practitioners and researchers. It integrates multiple contemporary discrete prompt optimizers while remaining agnostic to the underlying LLM implementation.

翻译：提示优化已成为提升大语言模型（LLM）在广泛任务中性能的关键技术。尽管众多研究论文已证明其有效性，但由于现有实现通常依赖于未维护且孤立的研究代码库，实际应用受到阻碍。为解决这一问题，我们提出了promptolution，这是一个统一且模块化的开源框架，为实践者和研究者提供了一个单一可扩展系统，其中包含了提示优化所需的所有组件。该框架集成了多种当代离散提示优化器，同时保持与底层LLM实现的无关性。