from __future__ import annotations

from evaluation.rag_metrics import (
    evaluate_answer,
    expected_phrase_matches,
)


def test_compact_unit_spacing_matches() -> None:
    assert expected_phrase_matches(
        "450MB",
        "Nazbieraných bolo približne 450 MB textu.",
    )


def test_llm_matches_large_language_model() -> None:
    assert expected_phrase_matches(
        "LLM",
        "Projekt používa veľký jazykový model.",
    )


def test_named_entities_matches_slovak_wording() -> None:
    assert expected_phrase_matches(
        "named entities",
        "Stáž sa venovala pomenovaným entitám.",
    )


def test_knowledge_graph_matches_slovak_wording() -> None:
    assert expected_phrase_matches(
        "knowledge graph",
        "Cieľom bolo zostaviť znalostný graf.",
    )


def test_multilingual_medical_triplet_phrase_matches_translation() -> None:
    assert expected_phrase_matches(
        "multilinguálna extrakcia trojíc z medicínskych dát",
        "Téma bola viacjazyčné extrahovanie trojíc z lekárskych dát.",
    )


def test_cesar_goal_matches_slovak_equivalent() -> None:
    assert expected_phrase_matches(
        "recognize unknown named entities",
        "Cieľom bolo rozpoznávať neznáme pomenované entity.",
    )
    assert expected_phrase_matches(
        "manually annotated training set",
        "Mal vytvoriť manuálne anotovanú trénovaciu množinu.",
    )
    assert expected_phrase_matches(
        "annotation schema",
        "Mal navrhnúť anotačnú schému.",
    )


def test_mteb_evaluation_can_match_descriptive_answer() -> None:
    assert expected_phrase_matches(
        "Hate Speech a MTEB evaluácia",
        (
            "Stáž zahŕňala slovenský hate speech a hodnotenie "
            "modelov sentence transformer."
        ),
    )


def test_ordinary_phrase_still_requires_ordered_local_match() -> None:
    assert not expected_phrase_matches(
        "slovenský internet",
        "Internetový projekt používa slovenský jazyk.",
    )


def test_multi_document_requires_two_gold_sources_not_all() -> None:
    question = {
        "category": "multi_document",
        "expected_answer_contains": ["RAG"],
        "expected_source_urls": [
            "https://example.test/a",
            "https://example.test/b",
            "https://example.test/c",
            "https://example.test/d",
        ],
        "should_answer": True,
    }
    answer = (
        "RAG sa nachádza vo viacerých dokumentoch.\n\n"
        "Zdroje:\n"
        "https://example.test/a\n"
        "https://example.test/c"
    )

    result = evaluate_answer(
        question,
        answer,
        tool_called=True,
    )

    assert result["source_match_count"] == 2
    assert result["source_required_count"] == 2
    assert result["strict_pass"] is True


def test_invalid_placeholder_source_urls_do_not_force_failure() -> None:
    question = {
        "category": "multi_document",
        "expected_answer_contains": ["strojový preklad"],
        "expected_source_urls": ["...", "...", "..."],
        "should_answer": True,
    }

    result = evaluate_answer(
        question,
        "Dokumenty riešia strojový preklad.",
        tool_called=True,
    )

    assert result["source_required_count"] == 0
    assert result["source_url_score"] == 1.0
    assert result["strict_pass"] is True


def test_single_document_still_requires_its_expected_source() -> None:
    question = {
        "category": "specific_fact",
        "expected_answer_contains": ["Prodigy"],
        "expected_source_urls": ["https://example.test/question"],
        "should_answer": True,
    }

    result = evaluate_answer(
        question,
        "Používa sa Prodigy.",
        tool_called=True,
    )

    assert result["source_required_count"] == 1
    assert result["strict_pass"] is False

def test_cesar_goal_matches_rozoznavat_variant() -> None:
    assert expected_phrase_matches(
        "recognize unknown named entities",
        "Cieľom bolo rozoznávať neznáme pomenované entity.",
    )