LLM-driven code evolution method library.
Project description
EvoToolkit
LLM-driven solution evolutionary optimization toolkit
EvoToolkit is a Python library that leverages Large Language Models (LLMs) to evolve solutions for optimization problems. It combines the power of evolutionary algorithms with LLM-based solution generation and refinement.
Installation
pip install evotoolkit
Note: The package is installed as evotoolkit but imported as evotool:
import evotool # Note: import name is different from package name
Quick Start
import evotool
from evotool.task.python_task.scientific_regression import ScientificRegressionTask
from evotool.task.python_task import EvoEngineerPythonInterface
from evotool.tools import HttpsApi
# 1. Create a task
task = ScientificRegressionTask(dataset_name="bactgrow")
# 2. Create an interface
interface = EvoEngineerPythonInterface(task)
# 3. Solve with LLM
llm_api = HttpsApi(
api_url="https://api.openai.com/v1/chat/completions",
key="your-api-key-here",
model="gpt-4o"
)
result = evotool.solve(
interface=interface,
output_path='./results',
running_llm=llm_api,
max_generations=5
)
Features
- 🤖 LLM-Driven Evolution: Use language models to generate and evolve solutions
- 🔬 Multiple Algorithms: EoH, EvoEngineer, and FunSearch
- 🌍 Task-Agnostic: Supports code, text, math expressions, etc.
- 🎯 Extensible: Easy-to-extend task system
- 🔌 Simple API: High-level
evotool.solve()function
Documentation
Full documentation: https://evotoolkit.readthedocs.io/
License
MIT License
Project details
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