| # Configuration for function minimization example | |
| max_iterations: 10 | |
| checkpoint_interval: 5 | |
| # LLM configuration | |
| llm: | |
| primary_model: "gemini-2.5-flash-lite" | |
| # primary_model: "gpt-5-mini" | |
| # primary_model: "llama3.1-8b" | |
| primary_model_weight: 0.8 | |
| secondary_model: "gemini-2.5-flash" | |
| # secondary_model: "llama-4-scout-17b-16e-instruct" | |
| # secondary_model: "gpt-5-nano" | |
| secondary_model_weight: 0.2 | |
| api_base: "https://generativelanguage.googleapis.com/v1beta/openai/" | |
| # api_base: "https://api.cerebras.ai/v1" | |
| # api_base: "https://api.openai.com/v1" | |
| temperature: 0.7 | |
| max_tokens: 16000 | |
| timeout: 120 | |
| # Prompt configuration | |
| prompt: | |
| system_message: "You are an expert programmer specializing in optimization algorithms. Your task is to improve a function minimization algorithm to find the global minimum of a complex function with many local minima. The function is f(x, y) = sin(x) * cos(y) + sin(x*y) + (x^2 + y^2)/20. Focus on improving the search_algorithm function to reliably find the global minimum, escaping local minima that might trap simple algorithms." | |
| # Database configuration | |
| database: | |
| population_size: 50 | |
| archive_size: 20 | |
| num_islands: 3 | |
| elite_selection_ratio: 0.2 | |
| exploitation_ratio: 0.7 | |
| # embedding_model: "text-embedding-3-small" | |
| similarity_threshold: 0.99 | |
| # Evaluator configuration | |
| evaluator: | |
| timeout: 60 | |
| cascade_thresholds: [1.3] | |
| parallel_evaluations: 3 | |
| # Evolution settings | |
| diff_based_evolution: true | |
| max_code_length: 20000 | |