"""Data Transfer Objects — configuration and results."""
from __future__ import annotations

from dataclasses import dataclass, field
from typing import Any


@dataclass
class OptimizationConfig:
    """Complete configuration for a PROMETHEUS run."""

    # --- Prompt ---
    seed_prompt: str
    task_description: str

    # --- Models ---
    task_model: str = "openai/gpt-4o-mini"
    judge_model: str = "openai/gpt-4o"
    proposer_model: str = "openai/gpt-4o"
    synth_model: str = "openai/gpt-4o"

    # --- Per-model API overrides (optional, fall back to global api_base/api_key_env) ---
    task_api_base: str | None = None
    task_api_key_env: str | None = None
    judge_api_base: str | None = None
    judge_api_key_env: str | None = None
    proposer_api_base: str | None = None
    proposer_api_key_env: str | None = None
    synth_api_base: str | None = None
    synth_api_key_env: str | None = None

    # --- Evolution parameters ---
    max_iterations: int = 30
    n_synthetic_inputs: int = 20
    minibatch_size: int = 5
    perfect_score: float = 1.0

    # --- Reproducibility ---
    seed: int = 42

    # --- Error handling ---
    max_retries: int = 3
    retry_delay_base: float = 1.0
    circuit_breaker_threshold: int = 5
    error_strategy: str = "retry"  # skip | retry | abort

    # --- Output ---
    output_path: str = "output.yaml"
    verbose: bool = False


@dataclass
class OptimizationResult:
    """Result of a complete optimization."""

    optimized_prompt: str
    initial_prompt: str
    iterations_used: int
    total_llm_calls: int
    initial_score: float
    final_score: float
    improvement: float
    history: list[dict[str, Any]] = field(default_factory=list)