from __future__ import annotations

from dataclasses import dataclass
from typing import Any, Dict

from .dsl import LocalProblem, PlanDelta
from .safety import verify_plan


@dataclass
class PlanResult:
    """Outcome from planning, including a safe delta and a proof flag."""

    plan_delta: PlanDelta
    proof_valid: bool
    justification: str


class ShadowPlanner:
    """A lightweight shadow planner that runs in parallel to the executor.

    For this MVP, it generates a conservative delta by slightly increasing
    resource buffers to create a safe alternative plan if the primary plan is
    infeasible with respect to LocalProblem.risk_budget.
    """

    def __init__(self, local_problem: LocalProblem):
        self.local_problem = local_problem

    def plan(self, primary_delta: PlanDelta) -> PlanResult:
        # Very simple heuristic: if risk_budget is low, persevere using a safer delta.
        risk = float(self.local_problem.risk_budget or 0.0)
        safe_delta = PlanDelta(delta={"safe_buffer": max(0.0, risk * 0.5)}, version=primary_delta.version + 1, metadata={"owner": "shadow"})

        # Verify safety using the same (mocked) verify_plan hook
        is_safe = verify_plan(self.local_problem, safe_delta)
        justification = "Shadow plan generated" if is_safe else "Shadow plan could not be validated safely"
        return PlanResult(plan_delta=safe_delta, proof_valid=is_safe, justification=justification)