"""Minimal CatOpt bridge scaffolding for NovaPlan MVP.

This module provides tiny, well-scoped helpers to map NovaPlan primitives
to a canonical CatOpt-like representation suitable for interoperability
in MVP experiments.
"""
from __future__ import annotations

from dataclasses import dataclass
from typing import Any, Dict, Optional

from nova_plan.contracts import PlanDelta
from nova_plan.planner import LocalProblem


@dataclass
class ObjectI:
    """Canonical object representation (per-agent LocalProblem).

    This is a lightweight wrapper intended for interop exploration.
    """

    id: str
    payload: Dict[str, Any]


@dataclass
class Morphism:
    """Canonical morphism carrying summarized signals or delta information."""

    source: str
    target: str
    data: Dict[str, float]  # summarized signals or delta payload
    version: int = 1
    contract_id: str = "default"


def to_object(local: LocalProblem) -> ObjectI:
    """Map a LocalProblem to a canonical ObjectI representation."""
    payload = {
        "variables": local.variables,
        "constraints": local.constraints,
        "id": local.id,
    }
    return ObjectI(id=local.id, payload=payload)


def delta_to_morphism(delta: PlanDelta, source: str = "local", target: str = "global", contract_id: Optional[str] = None) -> Morphism:
    """Convert a PlanDelta into a canonical Morphism."""
    return Morphism(
        source=delta.agent_id or source,
        target=target,
        data=delta.delta,
        version=1,
        contract_id=contract_id or delta.__dict__.get("contract_id", "default"),
    )


def bridge_example():
    """Small helper to illustrate a mapping between NovaPlan and CatOpt forms.

    This is intentionally lightweight and for demonstration in tests/examples.
    Returns a tuple of (ObjectI, Morphism).
    """
    # Minimal synthetic LocalProblem
    lp = LocalProblem(id="demo-agent", objective=lambda v, s: sum(v.values()) + sum(s.values()), variables={"a": 1.0}, constraints={})
    obj = to_object(lp)
    # Fake delta
    delta = {"a": -0.1}
    import time
    d = PlanDelta(agent_id=lp.id, delta=delta, timestamp=time.time())
    morph = delta_to_morphism(d, source=lp.id)
    return obj, morph


__all__ = ["ObjectI", "Morphism", "to_object", "delta_to_morphism", "bridge_example"]