"""Tests für den Semantic-Validator-Layer."""

from __future__ import annotations

import asyncio

import pytest

from compliance.services.specialist_agents import AgentInput, ImpressumAgent
from compliance.services.specialist_agents._semantic_validator import (
    STANDARD_LABELS,
    build_rename_action,
    standard_label,
    validate_present,
)


def _run(coro):
    return asyncio.get_event_loop().run_until_complete(coro)


def test_standard_labels_cover_impressum_fields():
    """Alle Impressum-Pflichtangaben müssen ein Standard-Label haben."""
    for fid in (
        "kontakt_telefon", "kontakt_email", "vertretungsberechtigte",
        "handelsregister", "ust_id", "name_anbieter",
    ):
        assert fid in STANDARD_LABELS, f"missing standard label: {fid}"


def test_build_rename_action_includes_old_and_new():
    a = build_rename_action("kontakt_telefon", "Telefonnr.")
    assert "Telefonnr." in a
    assert "Telefon" in a
    assert "Best-Practice" in a or "Umbenennung" in a


def test_standard_label_falls_back_to_field_id():
    assert standard_label("kontakt_telefon") == "Telefon"
    assert standard_label("ghost_field") == "ghost_field"


def test_validate_present_short_text_returns_empty():
    out = _run(validate_present(
        "x", [("kontakt_telefon", "Telefon")],
    ))
    assert out == {}


def test_validate_present_no_fields_returns_empty():
    out = _run(validate_present("Long impressum text" * 100, []))
    assert out == {}


def test_semantic_demotion_high_to_low(monkeypatch):
    """Wenn LLM bestätigt dass Pflichtangabe da ist: HIGH→LOW.

    Test-Setup: Impressum-Text OHNE jegliche Telefon-Markierung
    (Pattern matched nicht). LLM-Mock behauptet aber 'Funkanschluss'
    wäre ein abweichendes Label für die Telefonnummer.
    """
    from compliance.services.specialist_agents._escalation import (
        EscalationResult, SourceType,
    )
    from compliance.services.specialist_agents._base import EscalationLog

    async def _fake_cascade(sys_prompt, user_prompt,
                              expect_json=True, skip_ovh=False):
        # Nur auf den SVL-Prompt reagieren
        if "FEHLENDE PFLICHTANGABEN" not in user_prompt:
            return None, []
        log = EscalationLog(
            stage=SourceType.LLM_LOCAL, model="qwen2.5:7b",
            duration_ms=42, success=True,
        )
        res = EscalationResult(
            content='{"results":[]}',
            stage=SourceType.LLM_LOCAL,
            model="qwen2.5:7b",
            log=log,
            parsed={"results": [{
                "field_id": "kontakt_telefon",
                "found": True,
                "label_used": "Funkanschluss",
                "evidence": "Funkanschluss 0761/123456",
                "confidence": 0.9,
            }]},
        )
        return res, [log]
    monkeypatch.setattr(
        "compliance.services.specialist_agents._semantic_validator.cascade",
        _fake_cascade,
    )
    monkeypatch.setattr(
        "compliance.services.specialist_agents.impressum.agent.cascade",
        _fake_cascade,
    )
    # Text OHNE Telefon-Label → MC matched nicht → HIGH-Finding
    text = (
        "Beispiel GmbH\nMusterstr. 1\n12345 Berlin\n"
        "E-Mail: x@y.de\nFunkanschluss 0761/123456\n"
        "Geschäftsführer: Max Mustermann\n"
        "Handelsregister Berlin HRB 12345\n"
        "USt-IdNr: DE123456789"
    )
    agent = ImpressumAgent()
    out = _run(agent.evaluate(AgentInput(doc_type="impressum", text=text)))
    telefon_findings = [f for f in out.findings
                        if f.field_id == "kontakt_telefon"]
    assert telefon_findings, "expected MC-miss → finding"
    f = telefon_findings[0]
    # Erwartet: SVL hat demoted zu LOW
    assert f.severity == "LOW", (
        f"Erwartet: LOW nach semantic-demote, got: {f.severity}. "
        f"Finding: {f}"
    )
    assert f.severity_reason == "label_mismatch"
    assert "Funkanschluss" in f.action
    assert "Telefon" in f.action