OpenEvolve is an open-source evolutionary coding agent that uses large language models (LLMs) to iteratively improve programs. It implements a MAP-Elites quality-diversity algorithm with island-based evolution, supporting multiple LLM backends (OpenAI, Claude Code, etc.) and a cascade evaluation pattern. The system accepts a user-provided initial program and an evaluator script, then repeatedly mutates the program via LLM-generated SEARCH/REPLACE diffs or full rewrites, evaluates the fitness, and maintains a diverse population across feature dimensions. The core architecture is a library with a CLI entry point (`openevolve-run`), a high-level API (`run_evolution`, `evolve_function`, `evolve_code`), and a controller that orchestrates the evolution loop, prompt sampling, LLM inference, parallel evaluation, and database storage. The repository includes 20+ diverse examples ranging from algorithm optimization (AlgoTune, TSP, circle packing) to mathematical discovery (Heilbronn, kissing number) and hardware-specific kernel tuning (MLX Metal, MLIR). The codebase is well-structured with extensive unit and integration tests, typed configuration, and a modular design that separates concerns (evaluator, LLM, database, prompt templates). It is actively maintained with frequent commits and responsive issue triage.