SakanaAI/ShinkaEvolve

Health v2 · maintenance only

Adoption not part of the score

1414 stars · 281 forks observed · 2026-09-27

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

ShinkaEvolve is a Python framework that combines LLMs with evolutionary algorithms to automatically evolve and improve scientific code. It maintains a population of programs with LLMs acting as mutation operators, supporting async evaluation, archive-based search, and local or SLURM cluster execution.

Use cases

• evolve scientific code with llm-guided mutation
• run open-ended program evolution experiments
• optimize algorithms like circle packing automatically
• use llms as mutation operators for evolutionary search
• scale code evolution runs on a slurm cluster
• integrate program evolution into coding agents

When to choose

• you want sample-efficient, LLM-driven evolutionary optimization of code
• you need reproducible, resumable evolution runs with a WebUI for inspection
• you want to run evolution locally or on clusters with Hydra/SLURM support

When to avoid

• you need a general-purpose AutoML or hyperparameter tuning tool
• your task doesn't involve evolving or generating code
• you can't access LLM APIs or local models for mutation

Facets

framework · maturity active

agent-framework llm-inference machine-learning cli workflow-automation artificial-intelligence large-language-models developer-tools data-science python cli evolutionary-algorithms llm-guided-search program-synthesis scientific-discovery code-evolution hydra slurm ai-agents linux macos docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="SakanaAI/ShinkaEvolve")