This article introduces OpenEvolve, an open-source implementation of Google DeepMind's AlphaEvolve, a system that leverages Large Language Models (LLMs) in an evolutionary framework to generate and optimize code. OpenEvolve allows users to evolve entire codebases by iteratively creating modifications using LLMs, evaluating them with automated metrics, and selecting promising solutions through an evolutionary process. The article details OpenEvolve's architecture, highlighting its key components like the Prompt Sampler and LLM Ensemble, and provides examples demonstrating its ability to achieve results comparable to AlphaEvolve in complex problems such as circle packing and function minimization, showcasing the evolution from simpler algorithms to more sophisticated solutions. It also discusses the importance of LLM performance and diversity for successful evolution and provides guidance on how to install and use the software for developing and improving algorithms.