"""rwfx 结构化抽取「纯树·单父节点」确定性兜底测试。

rwfx 全链是一棵树（除预期行为↔驱动因素 1:1，其余皆 1:N），任何节点只有一个父节点、绝无
多对一/汇聚。弱模型常给「叙事」连多个驱动因素 → 乱线。``_collapse_to_single_parent`` 兜底把
每个节点的多父入边收敛到紧邻上一层的单一父节点。
"""

from __future__ import annotations

from app.gateway.routers.flow_extract import _collapse_to_single_parent
from deerflow.agents.roundtable_orchestrator.extraction_spec import (
    chain_level_rank,
    is_single_parent_chain,
)


def test_is_single_parent_chain() -> None:
    assert is_single_parent_chain("6BF") is True
    assert is_single_parent_chain("rwfx") is True
    assert is_single_parent_chain("rwfx-A") is True  # 多智能体 -A 后缀也认
    assert is_single_parent_chain("7BF") is False  # xdfx 有「脆弱点→策略」汇聚，非纯树
    assert is_single_parent_chain("3Q") is False  # 未写实业务保守不收敛
    assert is_single_parent_chain(None) is False


def test_chain_level_rank_rwfx() -> None:
    rank = chain_level_rank("6BF")
    assert rank == {"任务": 0, "目的": 1, "行为体": 2, "预期行为": 3, "驱动因素": 4, "叙事": 5}


def _rwfx_graph_with_bad_narrative() -> dict:
    # 叙事 s1 错误地连了 2 个驱动因素(上一层) + 1 个行为体(更上层)，应被收敛成单父。
    return {
        "title": "t",
        "nodes": [
            {"id": "n1", "group": "任务"},
            {"id": "m1", "group": "目的"},
            {"id": "a1", "group": "行为体"},
            {"id": "b1", "group": "预期行为"},
            {"id": "b2", "group": "预期行为"},
            {"id": "d1", "group": "驱动因素"},
            {"id": "d2", "group": "驱动因素"},
            {"id": "s1", "group": "叙事"},
        ],
        "edges": [
            {"from": "n1", "to": "m1"},
            {"from": "m1", "to": "a1"},
            {"from": "a1", "to": "b1"},
            {"from": "a1", "to": "b2"},
            {"from": "b1", "to": "d1"},
            {"from": "b2", "to": "d2"},
            {"from": "d1", "to": "s1"},  # 叙事多父：驱动因素 d1
            {"from": "d2", "to": "s1"},  # 叙事多父：驱动因素 d2
            {"from": "a1", "to": "s1"},  # 叙事多父：行为体 a1（跨层）
        ],
    }


def test_collapse_narrative_multi_parent_to_single() -> None:
    out = _collapse_to_single_parent(_rwfx_graph_with_bad_narrative(), "6BF")
    s1_parents = [e["from"] for e in out["edges"] if e["to"] == "s1"]
    # 叙事只剩一个父；应保留紧邻上一层（驱动因素），不保留更上层的行为体；同层保留第一个。
    assert s1_parents == ["d1"]
    # 其余每个非根节点仍恰一个父（1:1 / 1:N 本就单父，不受影响）。
    for nid in ("m1", "a1", "b1", "b2", "d1", "d2"):
        assert len([e for e in out["edges"] if e["to"] == nid]) == 1
    # 根节点无入边。
    assert [e for e in out["edges"] if e["to"] == "n1"] == []


def test_collapse_noop_when_already_tree() -> None:
    # 每个节点本就单父 → 边数不变、内容不变。
    graph = {
        "nodes": [{"id": "n1", "group": "任务"}, {"id": "m1", "group": "目的"}, {"id": "a1", "group": "行为体"}],
        "edges": [{"from": "n1", "to": "m1"}, {"from": "m1", "to": "a1"}],
    }
    out = _collapse_to_single_parent(graph, "6BF")
    assert out["edges"] == [{"from": "n1", "to": "m1"}, {"from": "m1", "to": "a1"}]