"""Central configuration: single source of truth for thresholds, budgets, routing.

Loads from environment / .env via pydantic-settings. Every tunable knob lives
here so the rest of the package reads defaults from one place.
"""

from __future__ import annotations

from pydantic import Field
from pydantic_settings import BaseSettings, SettingsConfigDict


class StealthThresholds(BaseSettings):
    """Hard gate thresholds for human-imperceptibility (from the research)."""

    psnr_min: float = 38.0
    ssim_min: float = 0.94
    lpips_max: float = 0.10
    delta_e_p95_max: float = 2.0  # measured on the text region only


# Presets for the stealth SWEEP: strict = barely noticeable, loose = tolerant of
# visible text. Used to plot the attack-strength vs human-visibility frontier.
STEALTH_PRESETS: dict[str, dict[str, float]] = {
    "strict": {"psnr_min": 38.0, "ssim_min": 0.94, "lpips_max": 0.10, "delta_e_p95_max": 2.0},
    "medium": {"psnr_min": 32.0, "ssim_min": 0.90, "lpips_max": 0.20, "delta_e_p95_max": 5.0},
    "loose": {"psnr_min": 26.0, "ssim_min": 0.82, "lpips_max": 0.40, "delta_e_p95_max": 12.0},
}


def stealth_preset(level: str) -> StealthThresholds:
    return StealthThresholds(**STEALTH_PRESETS[level])


class Budget(BaseSettings):
    """Query/spend caps. All paid pressure is isolated to Tier B."""

    max_blackbox_queries_per_image: int = 50
    top_k_to_validate: int = 4  # gate-passing candidates sent to Tier B
    hard_usd_cap_per_image: float = 0.50


class RobustnessSim(BaseSettings):
    """Scraper-preprocessing simulation baked into fitness eval."""

    jpeg_quality: int = 85
    gaussian_blur_radius: float = 0.5


class OptimizerConfig(BaseSettings):
    """Tier A search shape.

    Grid size = decoys x grid_positions x grid_colors x |grid_font_px|. Each cell
    scores every surrogate, so keep the product modest: with ~2s/call surrogates a
    grid of ~50 cells is ~2 min/image. `grid_positions`/`grid_colors` cap how many
    of the available positions/color strategies the coarse grid explores.
    """

    decoy_shortlist_size: int = 4
    grid_font_px: tuple[int, ...] = (12, 20)
    grid_positions: int = 2
    grid_colors: int = 2
    grid_alpha: float = 0.25
    tier_a_workers: int = 4
    evo_population: int = 6
    evo_generations: int = 4
    alpha_range: tuple[float, float] = (0.10, 0.35)
    font_px_range: tuple[int, int] = (8, 24)
    early_stop_epsilon: float = 1e-3
    early_stop_patience: int = 2


class Settings(BaseSettings):
    """Top-level settings, populated from environment / .env."""

    model_config = SettingsConfigDict(
        env_file=".env", env_file_encoding="utf-8", extra="ignore"
    )

    # --- OpenRouter (Tier B targets + primary embeddings) ---
    openrouter_api_key: str = Field(default="", alias="OPENROUTER_API_KEY")
    openrouter_base_url: str = "https://openrouter.ai/api/v1"
    blackbox_target_models: tuple[str, ...] = (
        "openai/gpt-5.5",
        "google/gemini-3.5-flash",
    )
    embedding_model: str = "openai/text-embedding-3-small"

    # --- GPU service endpoints (legacy black-box CLI) ---
    # Override via the KLAUS3_* env vars (see .env.example) to point at your host.
    klaus3_qwen_base_url: str = Field(
        default="http://127.0.0.1:8081/v1", alias="KLAUS3_QWEN_BASE_URL"
    )
    klaus3_gemma4b_base_url: str = Field(
        default="http://127.0.0.1:8082/v1", alias="KLAUS3_GEMMA4B_BASE_URL"
    )
    klaus3_gemma12b_base_url: str = Field(
        default="http://127.0.0.1:8080/v1", alias="KLAUS3_GEMMA12B_BASE_URL"
    )
    klaus3_vision_service_url: str = Field(
        default="http://127.0.0.1:8090", alias="KLAUS3_VISION_SERVICE_URL"
    )
    # Surrogate VLMs used for the free Tier A search.
    surrogate_models: tuple[str, ...] = ("qwen-3.5-4b", "gemma-4-4b")

    # --- aggregation ---
    # "mean" = robust (poison that generalizes); "min" = fool-all (worst case).
    aggregation: str = "mean"

    # --- sub-configs ---
    stealth: StealthThresholds = Field(default_factory=StealthThresholds)
    budget: Budget = Field(default_factory=Budget)
    robustness: RobustnessSim = Field(default_factory=RobustnessSim)
    optimizer: OptimizerConfig = Field(default_factory=OptimizerConfig)

    # --- paths ---
    cache_dir: str = ".cache"
    artifacts_dir: str = "artifacts"


_settings: Settings | None = None


def get_settings(reload: bool = False) -> Settings:
    """Process-wide singleton accessor for Settings."""
    global _settings
    if _settings is None or reload:
        _settings = Settings()
    return _settings