"""Agent sprint ranker slot — placeholder for Principle Gate / Actor execution."""

from __future__ import annotations

from typing import Any

from steering.eval_context import SteeringEvalContext
from steering.proposals.sprint_commit_context import (
    RankedSprintCommitCandidate,
    SprintCommitCandidate,
    register_sprint_commit_ranker,
)
from steering.proposals.sprint_commit_heuristic_v0 import HeuristicV0SprintCommitRanker

_FALLBACK = HeuristicV0SprintCommitRanker()


class AgentV1SprintCommitRanker:
    """
    Agent-gestütztes Ranking — noch nicht aktiv (Principle Gate).

    Kontext kommt aus Snapshot/Operating Context; Scoring über auditierten Actor,
    nicht aus hardcodiertem Prompt. Bis Freigabe: Fallback auf heuristic_v0.
    """

    key = "agent_v1"

    def rank(
        self,
        ctx: SteeringEvalContext,
        *,
        candidates: list[SprintCommitCandidate],
        read_models: dict[str, Any],
        target_work_cycle_id: str,
    ) -> list[RankedSprintCommitCandidate]:
        # TODO(P6+): Actor-Slot + Governance-Pack; KI wählt Subset + Begründung
        ranked = _FALLBACK.rank(
            ctx,
            candidates=candidates,
            read_models=read_models,
            target_work_cycle_id=target_work_cycle_id,
        )
        return [
            RankedSprintCommitCandidate(
                candidate=row.candidate,
                rank=row.rank,
                score=row.score,
                reason_code=row.reason_code,
                summary=f"{row.summary} (Agent-Ranker: Fallback heuristic_v0)",
                factors=row.factors
                + [
                    {
                        "code": "ranker_fallback",
                        "weight": 0,
                        "label": "agent_v1 noch nicht freigegeben",
                    }
                ],
                ranker_key="agent_v1_fallback",
            )
            for row in ranked
        ]


register_sprint_commit_ranker(AgentV1SprintCommitRanker())