"""Application configuration with Pydantic models."""

from pydantic import BaseModel, Field


class EscalationConfig(BaseModel):
    """Escalation engine parameters."""
    rate: float = 0.05
    initial_batch_size: int = 40
    max_images: int = 200
    max_audio_clips: int = 50
    asset_swap_min: float = 0.5  # seconds (at high intensity)
    asset_swap_max: float = 15.0  # seconds (at low intensity)
    voice_mean_interval: float = 60.0  # Poisson mean at intensity 0
    silence_gap_min: float = 2.0
    silence_gap_max: float = 30.0
    fake_calm_chance: float = 0.08  # probability per phase update
    fake_calm_duration_min: float = 10.0
    fake_calm_duration_max: float = 30.0
    cluster_burst_chance: float = 0.1
    cluster_burst_count_min: int = 2
    cluster_burst_count_max: int = 5


class ModelConfig(BaseModel):
    """AI model identifiers and generation parameters."""
    sdxl_model_id: str = "stabilityai/sdxl-turbo"
    sdxl_steps: int = 4
    sdxl_guidance_scale: float = 0.0
    sdxl_width: int = 512
    sdxl_height: int = 512
    xtts_model: str = "tts_models/multilingual/multi-dataset/xtts_v2"
    xtts_language: str = "en"


class AppConfig(BaseModel):
    """Top-level application config."""
    host: str = "0.0.0.0"
    port: int = 8400
    device: str = "cuda"
    assets_dir: str = "assets"
    samples_dir: str = "samples"
    escalation: EscalationConfig = Field(default_factory=EscalationConfig)
    models: ModelConfig = Field(default_factory=ModelConfig)


config = AppConfig()