"""Unit tests for LlmPipeline with a mocked LLM client.

The pipeline no longer constructs an embedding provider: change detection moved
to the deterministic RegulationDiffer, and the LLM is called only to explain
changes that determinism already located. These tests pin that gating contract.
"""
from __future__ import annotations

from unittest.mock import MagicMock, patch


def _make_pipeline(content: str | None = None):
    """Build a pipeline whose LLM client is a mock returning `content`."""
    default = (
        '{"obligations":[{"text":"test obligation","deontic":"must","subject":"OEM",'
        '"object":"system","condition":""}],"deadlines":[{"date":"2026-07-01",'
        '"description":"实施截止"}],"scope":"适用于M1类车辆","penalties":"罚款",'
        '"impact_level":"high"}'
    )
    with patch("app.infrastructure.perception.llm_pipeline.get_llm_client") as mock_llm_fn:
        mock_client = MagicMock()
        mock_client.chat.return_value = MagicMock(content=content or default)
        mock_llm_fn.return_value = mock_client

        from app.infrastructure.perception.llm_pipeline import LlmPipeline
        return LlmPipeline(), mock_client


def test_extract_structure_returns_dict():
    """Structure extraction still returns the enrichment keys callers expect."""
    pipeline, _ = _make_pipeline()
    event = {
        "id": "evt-001",
        "standard_code": "GB 18384-2025",
        "title": "电动汽车安全要求",
        "summary": "新增 IP67 级别防护",
        "source_label": "CATARC",
        "tags": ["电池安全"],
    }
    result = pipeline.extract_structure(event)
    assert isinstance(result, dict)
    assert "obligations" in result
    assert "impact_level" in result


def test_assess_impact_returns_list():
    """Impact assessment still returns a list of affected documents."""
    pipeline, _ = _make_pipeline(
        '[{"doc_id":"d1","doc_name":"Safety Manual","score":0.85,'
        '"key_clauses":"§4.2","recommendation":"更新第4章"}]'
    )
    mock_retrieval = MagicMock()
    chunk = MagicMock()
    chunk.doc_id = "d1"
    chunk.doc_title = "Safety Manual"
    chunk.score = 0.85
    chunk.text = "relevant text"
    chunk.section_title = "§4.2"
    mock_retrieval.retrieve.return_value = [chunk]
    event = {
        "standard_code": "GB 18384-2025",
        "title": "电动汽车安全要求",
        "obligations": [{"text": "OEM shall comply"}],
    }
    assert isinstance(pipeline.assess_impact(event, mock_retrieval), list)


def test_compute_diff_no_change_costs_no_llm_call():
    """Identical text must short-circuit before reaching the model."""
    pipeline, mock_client = _make_pipeline()
    mock_client.chat.reset_mock()

    result = pipeline.compute_diff("第一条 保持不变的条款。", "第一条 保持不变的条款。")

    assert result["changed_sections"] == []
    assert "No substantive changes" in result["change_summary"]
    mock_client.chat.assert_not_called()


def test_compute_diff_classifies_a_real_change():
    """A gated change is classified and the model's legal_effect is surfaced."""
    pipeline, _ = _make_pipeline(
        '{"change_type":"tightened","legal_effect":"Requirement tightened."}'
    )
    result = pipeline.compute_diff(
        "第三条 生产企业应当每年开展一次安全评估。",
        "第三条 生产企业宜每年开展一次安全评估。",
    )

    sections = result["changed_sections"]
    assert len(sections) == 1
    assert sections[0]["change_type"] == "tightened"
    assert sections[0]["summary"] == "Requirement tightened."


def test_numeric_change_overrides_the_model_label():
    """A moved number wins over the model, which routinely calls it 'clarified'."""
    pipeline, _ = _make_pipeline(
        '{"change_type":"clarified","legal_effect":"Minor wording update."}'
    )
    result = pipeline.compute_diff(
        "第二条 车辆制动系统应在30米内完全停止。",
        "第二条 车辆制动系统应在20米内完全停止。",
    )

    section = result["changed_sections"][0]
    assert section["numeric_changed"] is True
    assert section["change_type"] == "numeric"


def test_cosmetic_change_is_never_sent_to_the_model():
    """Punctuation-only edits are recorded but must not cost a model call."""
    pipeline, mock_client = _make_pipeline()
    mock_client.chat.reset_mock()

    result = pipeline.compute_diff(
        "第五条 本标准由全国汽车标准化技术委员会归口管理。",
        "第五条 本标准由全国汽车标准化技术委员会归口管理",
    )

    assert len(result["changed_sections"]) == 1
    mock_client.chat.assert_not_called()


def test_llm_failure_preserves_the_deterministic_record():
    """A model error must not discard a change deterministic analysis proved real."""
    pipeline, mock_client = _make_pipeline()
    mock_client.chat.side_effect = RuntimeError("gateway down")

    result = pipeline.compute_diff(
        "第二条 车辆制动系统应在30米内完全停止。",
        "第二条 车辆制动系统应在20米内完全停止。",
    )

    section = result["changed_sections"][0]
    assert section["numeric_changed"] is True
    assert section["change_type"] == "numeric"
    assert section["summary"] == ""
    assert "第二条" in section["old_text"]


def test_only_gated_paragraphs_reach_the_model():
    """One significant change among cosmetic ones yields exactly one model call."""
    pipeline, mock_client = _make_pipeline(
        '{"change_type":"tightened","legal_effect":"Tighter limit."}'
    )
    mock_client.chat.reset_mock()

    old = "\n".join([
        "第一条 本标准规定了车辆制动系统的技术要求。",
        "第二条 车辆制动系统应在30米内完全停止。",
        "第三条 本标准由全国汽车标准化技术委员会归口管理。",
    ])
    new = "\n".join([
        "第一条 本标准规定了车辆制动系统的技术要求。",
        "第二条 车辆制动系统应在20米内完全停止。",
        "第三条 本标准由全国汽车标准化技术委员会归口管理",
    ])

    result = pipeline.compute_diff(old, new)

    # Two paragraphs changed; only the numeric one clears the gate.
    assert len(result["changed_sections"]) == 2
    assert mock_client.chat.call_count == 1