config.yaml

# Configuration for Real-Time Adaptive Signal Processing Example
max_iterations: 100
checkpoint_interval: 10
log_level: "INFO"

# LLM configuration
llm:
  primary_model: "gemini-2.5-flash-lite-preview-06-17"
  primary_model_weight: 0.8
  secondary_model: "gemini-2.5-flash"
  secondary_model_weight: 0.2
  api_base: "https://generativelanguage.googleapis.com/v1beta/openai/"
  temperature: 0.6
  top_p: 0.95
  max_tokens: 32000

# Prompt configuration
prompt:
  system_message: "You are an expert signal processing engineer specializing in real-time adaptive filtering algorithms. Your task is to improve a signal processing algorithm that filters volatile, non-stationary time series data using a sliding window approach. The algorithm must minimize noise while preserving signal dynamics with minimal computational latency and phase delay. Focus on the multi-objective optimization of: (1) Slope change minimization - reducing spurious directional reversals, (2) Lag error minimization - maintaining responsiveness, (3) Tracking accuracy - preserving genuine signal trends, and (4) False reversal penalty - avoiding noise-induced trend changes. Consider advanced techniques like adaptive filtering (Kalman filters, particle filters), multi-scale processing (wavelets, EMD), predictive enhancement (polynomial fitting, neural networks), and trend detection methods."
  num_top_programs: 3
  use_template_stochasticity: true

# Database configuration
database:
  population_size: 80
  archive_size: 30
  num_islands: 4
  elite_selection_ratio: 0.15
  exploitation_ratio: 0.65

# Evaluator configuration
evaluator:
  timeout: 120
  cascade_evaluation: true
  cascade_thresholds: [0.3, 0.6]
  parallel_evaluations: 4
  use_llm_feedback: false

# Evolution settings
diff_based_evolution: true
max_code_length: 60000