"""Optuna objective, search space, and diverse top-N selector (doc 06).

Owns the Bayesian search wiring. Must **not** know broker specifics — those
live in the instrument config. The objective samples parameters from the
declared search space, runs the engine, and returns a score; the selector
picks 2–3 **diverse** finalists (not the top-N-by-score, which are usually
near-clones of one peak).
"""
from .objective import Constraints, ObjectiveConfig, build_objective, score_metrics
from .search_space import SearchSpace, suggest_params
from .selector import select_diverse_topn, param_distance

__all__ = [
    "SearchSpace",
    "suggest_params",
    "ObjectiveConfig",
    "Constraints",
    "build_objective",
    "score_metrics",
    "select_diverse_topn",
    "param_distance",
]