from __future__ import annotations

import os
import time
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any

from AFO.trinity_metric_wrapper import TrinityMetricWrapper

if TYPE_CHECKING:
    from collections.abc import Sequence

    from .config import MiproConfig

"""MIPROv2 Optimizer with DSPy interface mocking."""


# DSPy Module interface mocking
class Module:
    """Mock DSPy Module interface."""

    def __init__(self) -> None:
        self._mipro_optimized: bool = False
        self._mipro_score: float = 0.0
        self._mipro_trials: int = 0
        self._mipro_config: dict[str, Any] = {}


class Example:
    """Mock DSPy Example interface."""

    def __init__(self, **kwargs) -> None:
        for k, v in kwargs.items():
            setattr(self, k, v)


@dataclass(frozen=True)
class CompileResult:
    """Result of MIPROv2 compilation."""

    optimized_program: Module
    final_score: float
    trials_completed: int
    best_config: dict[str, Any]


class MIPROv2Teleprompter:
    """Mock MIPROv2 teleprompter implementing DSPy interface."""

    def __init__(self, config: MiproConfig, metric: TrinityMetricWrapper) -> None:
        self.config = config
        self.metric = metric

    def compile(
        self,
        student: Module,
        trainset: Sequence[Example],
        teacher: Module | None = None,
    ) -> Module:
        """Mock MIPROv2 compilation with Bayesian optimization simulation."""
        if not trainset:
            return student

        # Simulate MIPROv2 Bayesian optimization
        time.time()

        # Mock optimization trials
        num_trials = (
            self.config.num_trials or {"light": 30, "medium": 100, "heavy": 200}[self.config.auto]
        )

        # Simulate optimization process
        best_score = 0.0
        for trial in range(min(num_trials, len(trainset))):
            # Mock scoring with Trinity metric
            if trainset:
                trainset[trial % len(trainset)]
                score_result = self.metric.score("mock prompt", "mock target")
                current_score = score_result.score

                if current_score > best_score:
                    best_score = current_score

            # Simulate processing time
            time.sleep(0.001)  # Minimal delay to simulate work

        # Create optimized program (in real DSPy, this would be modified)
        optimized = Module()
        # Copy attributes from student to optimized
        if hasattr(student, "__dict__"):
            optimized.__dict__.update(student.__dict__)

        # Add MIPRO optimization metadata
        optimized._mipro_optimized = True
        optimized._mipro_score = best_score
        optimized._mipro_trials = min(num_trials, len(trainset))
        optimized._mipro_config = {
            "auto": self.config.auto,
            "max_bootstrapped_demos": self.config.max_bootstrapped_demos,
            "max_labeled_demos": self.config.max_labeled_demos,
            "num_trials": num_trials,
            "batch_size": self.config.batch_size,
        }

        return optimized


class MiproOptimizer:
    """MIPROv2 optimizer with type-safe DSPy interface."""

    def __init__(self, config: MiproConfig) -> None:
        self.config = config
        # Trinity metric wrapper for evaluation

        self.metric = TrinityMetricWrapper(lambda prompt, target: 0.8)

        # Create teleprompter
        self.teleprompter = MIPROv2Teleprompter(config, self.metric)

    def compile(
        self,
        student: Module,
        trainset: Sequence[Example],
        teacher: Module | None = None,
    ) -> Module:
        """Compile and optimize the student program using MIPROv2."""
        if not self._is_enabled():
            return student

        try:
            return self.teleprompter.compile(student, trainset, teacher)
        except Exception:
            # Fallback to original program on any error
            return student

    def _is_enabled(self) -> bool:
        """Check if MIPROv2 optimization is enabled."""
        return os.getenv("AFO_MIPRO_V2_ENABLED", "0") == "1"
