Quick Start¶

Set up an OpenAI API key:
- Obtain an API key from OpenAI.
- Set the API key in your environment variables:
```
export OPENAI_API_KEY='your_api_key_here'
```

Running an Experiment

import os

from iohblade.experiment import Experiment
from iohblade.llm import Ollama_LLM
from iohblade.methods import LLaMEA, RandomSearch
from iohblade.benchmarks import BBOB_SBOX
from iohblade.loggers import ExperimentLogger

llm = Ollama_LLM("qwen2.5-coder:14b") #qwen2.5-coder:14b, deepseek-coder-v2:16b
budget = 50 #short budget for testing

RS = RandomSearch(llm, budget=budget) #Random Search baseline
LLaMEA_method = LLaMEA(llm, budget=budget, name="LLaMEA", n_parents=4, n_offspring=12, elitism=False) #LLamEA with 4,12 strategy
methods = [RS, LLaMEA_method]

problems = []
# include all SBOX_COST functions with 5 instances for training and 10 for final validation as the benchmark problem.
training_instances = [(f, i) for f in range(1,25) for i in range(1, 6)]
test_instances = [(f, i) for f in range(1,25) for i in range(5, 16)]
problems.append(BBOB_SBOX(training_instances=training_instances, test_instances=test_instances, dims=[5], budget_factor=2000, name=f"SBOX_COST"))
# Set up the experiment object with 5 independent runs per method/problem. (in this case 1 problem)
logger = ExperimentLogger("results/SBOX")
experiment = Experiment(methods=methods, problems=problems, runs=5, show_stdout=True, exp_logger=logger) #normal run
experiment() #run the experiment, all data is logged in the folder results/SBOX/

Monitoring experiment progress.
Run the included web-app that searches for all the experiments–running and completed–in the current-working-directory/results. It can be used to monitor progress of running experiment, inspect convergence of completed experiments and download best solution found so far.

To run the web app:
uv run iohblade-webapp
Read more here.

Examples¶

Additional examples can be found in our examples folder on GitHub.