"""Tests for EPUB search core helpers."""

from __future__ import annotations

import logging
from datetime import UTC, datetime
from os import environ
from pathlib import Path
from types import ModuleType
from typing import TYPE_CHECKING

import pytest
from sqlalchemy import create_engine, select
from sqlalchemy.orm import sessionmaker

from python.ebook_search.answer import answer_query
from python.ebook_search.bm25_corpus import (
    BM25Corpus,
    BM25CorpusUnavailableError,
    BM25Manifest,
    ensure_bm25_corpus,
    fetch_bm25_corpus_records,
    load_bm25_corpus,
    read_bm25_manifest,
    score_bm25_corpus,
    write_bm25_corpus,
)
from python.ebook_search.config import EbookSearchConfig, RerankConfig, load_config, normalize_embedding_model
from python.ebook_search.embeddings import MODEL_DIMENSIONS, ensure_embedding_models
from python.ebook_search.ingest import chunk_text, find_existing_source
from python.ebook_search.search import (
    SearchResponse,
    SearchResult,
    bm25_candidates,
    reciprocal_rank_fusion,
    retrieval_query_from_text,
)
from python.ebook_search.timing import RuntimeStep
from python.orm.richie import (
    EbookChapter,
    EbookChunk,
    EbookChunkEmbedding1024,
    EbookEmbeddingModel,
    EbookSource,
    RichieBase,
)

if TYPE_CHECKING:
    from pytest_mock import MockerFixture


def test_chunk_text_uses_overlap() -> None:
    chunks = chunk_text(" ".join(str(index) for index in range(100)), chunk_tokens=20, overlap_tokens=5)

    assert len(chunks) > 1
    assert chunks[0].token_start == 0
    assert chunks[1].token_start == 15
    assert all(chunk.token_count <= 20 for chunk in chunks)


def test_reciprocal_rank_fusion_combines_vector_and_bm25_rankings() -> None:
    vector_results = [
        SearchResult(chunk_id=1, text="a", source_title="A", score=0.9, vector_score=0.9),
        SearchResult(chunk_id=2, text="b", source_title="B", score=0.8, vector_score=0.8),
    ]
    lexical_results = [
        SearchResult(chunk_id=2, text="b", source_title="B", score=4.2, bm25_score=4.2),
        SearchResult(chunk_id=3, text="c", source_title="C", score=2.1, bm25_score=2.1),
    ]

    fused = reciprocal_rank_fusion(vector_results, lexical_results, rank_constant=60)

    assert [result.chunk_id for result in fused] == [2, 1, 3]
    assert fused[0].rank_source == "Hybrid"
    assert fused[0].vector_score == 0.8
    assert fused[0].bm25_score == 4.2
    assert fused[0].fused_score == fused[0].score


def test_find_existing_source_matches_path_or_hash() -> None:
    engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
    RichieBase.metadata.create_all(engine)
    with sessionmaker(bind=engine, expire_on_commit=False, future=True)() as session:
        source = EbookSource(
            title="Book",
            author=None,
            language=None,
            publisher=None,
            identifier=None,
            file_path="/old/book.epub",
            file_sha256="a" * 64,
            file_mtime=datetime.now(tz=UTC),
            file_size=10,
        )
        session.add(source)
        session.commit()

        assert find_existing_source(session, Path("/old/book.epub"), "b" * 64) == source
        assert find_existing_source(session, Path("/new/book.epub"), "a" * 64) == source


def test_bm25_corpus_uses_existing_search_text_without_duplicate_metadata() -> None:
    engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
    RichieBase.metadata.create_all(engine)
    with sessionmaker(bind=engine, expire_on_commit=False, future=True)() as session:
        source = EbookSource(
            title="Book",
            author="Author",
            language=None,
            publisher=None,
            identifier=None,
            file_path="/book.epub",
            file_sha256="a" * 64,
            file_mtime=datetime.now(tz=UTC),
            file_size=10,
        )
        session.add(source)
        session.flush()
        chapter = EbookChapter(source_id=source.id, spine_index=0, title="Chapter", href=None)
        session.add(chapter)
        session.flush()
        session.add(
            EbookChunk(
                id=1,
                source_id=source.id,
                chapter_id=chapter.id,
                chunk_index=0,
                text="content",
                token_start=0,
                token_count=1,
                page_label=None,
                content_sha256="b" * 64,
                search_text="Book Author Chapter content",
            )
        )
        session.commit()

        records, texts = fetch_bm25_corpus_records(session)

    assert texts == ["Book Author Chapter content"]
    assert records[0]["chunk_id"] == 1
    assert "bm25_text" not in records[0]


def test_reciprocal_rank_fusion_marks_hybrid_source() -> None:
    vector_results = [SearchResult(chunk_id=1, text="a", source_title="A")]
    lexical_results = [SearchResult(chunk_id=2, text="b", source_title="B")]

    fused = reciprocal_rank_fusion(vector_results, lexical_results, rank_constant=60)

    assert {result.rank_source for result in fused} == {"Hybrid"}


def test_search_response_sums_runtime_steps() -> None:
    response = SearchResponse(
        query="query",
        results=[],
        rank_label="Hybrid",
        timings=(
            RuntimeStep(name="A", duration_ms=1.25),
            RuntimeStep(name="B", duration_ms=2.75),
            RuntimeStep(name="Parallel detail", duration_ms=10.0, counts_toward_total=False),
        ),
    )

    assert response.total_runtime_ms == 4.0


def test_retrieval_query_keeps_entity_and_series_terms() -> None:
    assert retrieval_query_from_text("what does Damien Montgomery stand for in starship mage") == (
        "damien montgomery stand starship mage"
    )


def test_bm25_candidates_scores_whole_corpus(mocker: MockerFixture) -> None:
    record = {
        "chunk_id": 2,
        "text": "high",
        "source_title": "B",
        "source_author": None,
        "chapter_title": None,
        "page_label": None,
        "bm25_text": "high",
    }
    manifest = BM25Manifest(created_at=datetime.now(tz=UTC), db_updated_at=None, chunk_count=1)
    corpus = BM25Corpus(retriever=object(), records=(record,), manifest=manifest)
    captured: dict[str, object] = {}

    def fake_score_bm25_corpus(query, saved_corpus, *, limit):
        captured["query"] = query
        captured["corpus"] = saved_corpus
        captured["limit"] = limit
        return [(record, 1.5)]

    mocker.patch("python.ebook_search.search.load_bm25_corpus", side_effect=lambda _config: corpus)
    mocker.patch("python.ebook_search.search.score_bm25_corpus", side_effect=fake_score_bm25_corpus)
    config = EbookSearchConfig(rerank=RerankConfig(enabled=False))

    results = bm25_candidates("high", config)

    assert captured["query"] == "high"
    assert captured["corpus"] == corpus
    assert captured["limit"] == 120
    assert [result.chunk_id for result in results] == [2]
    assert [result.bm25_score for result in results] == [1.5]


def test_bm25_candidates_returns_empty_when_corpus_is_unavailable(mocker: MockerFixture, caplog) -> None:
    def fake_load_bm25_corpus(_config):
        raise BM25CorpusUnavailableError

    mocker.patch("python.ebook_search.search.load_bm25_corpus", side_effect=fake_load_bm25_corpus)
    config = EbookSearchConfig(rerank=RerankConfig(enabled=False))

    with caplog.at_level(logging.WARNING):
        results = bm25_candidates("high", config)

    assert results == []
    assert "ebook_bm25_index_unavailable_skipping" in caplog.text


def test_write_bm25_corpus_publishes_dated_generation(tmp_path) -> None:
    index_path = tmp_path / "bm25"
    index_path.mkdir()
    generations_path = index_path / "generations"
    generations_path.mkdir()
    old_generation = generations_path / "20260101T000000.000000Z"
    old_generation.mkdir()
    (old_generation / "sentinel").write_text("old", encoding="utf-8")
    (index_path / "current").symlink_to(Path("generations") / old_generation.name, target_is_directory=True)
    manifest = BM25Manifest(
        created_at=datetime(2026, 6, 12, 1, 2, 3, 456789, tzinfo=UTC),
        db_updated_at=None,
        chunk_count=0,
    )

    write_bm25_corpus(index_path, [], [], manifest)

    current_path = index_path / "current"
    assert current_path.is_symlink()
    assert current_path.readlink() == generations_path / "20260612T010203.456789Z"
    assert old_generation.is_dir()
    assert (old_generation / "sentinel").read_text(encoding="utf-8") == "old"
    assert (generations_path / "20260612T010203.456789Z").is_dir()
    assert read_bm25_manifest(index_path) == manifest


def test_write_bm25_corpus_keeps_current_generation_when_publish_fails(mocker: MockerFixture, tmp_path) -> None:
    index_path = tmp_path / "bm25"
    index_path.mkdir()
    generations_path = index_path / "generations"
    generations_path.mkdir()
    old_generation = generations_path / "20260101T000000.000000Z"
    old_generation.mkdir()
    (old_generation / "sentinel").write_text("old", encoding="utf-8")
    current_path = index_path / "current"
    current_path.symlink_to(Path("generations") / old_generation.name, target_is_directory=True)
    original_replace = Path.replace

    def fail_current_replace(self, target):
        if self.parent == index_path and self.name.startswith(".current.") and target == current_path:
            msg = "current publish failed"
            raise OSError(msg)
        return original_replace(self, target)

    mocker.patch.object(Path, "replace", fail_current_replace)
    manifest = BM25Manifest(
        created_at=datetime(2026, 6, 12, 1, 2, 3, 456789, tzinfo=UTC),
        db_updated_at=None,
        chunk_count=0,
    )

    with pytest.raises(OSError, match="current publish failed"):
        write_bm25_corpus(index_path, [], [], manifest)

    assert current_path.readlink() == Path("generations") / old_generation.name
    assert (old_generation / "sentinel").read_text(encoding="utf-8") == "old"
    assert not (generations_path / "20260612T010203.456789Z").exists()


def test_load_bm25_corpus_uses_current_generation(tmp_path) -> None:
    load_bm25_corpus.cache_clear()
    index_path = tmp_path / "bm25"
    manifest = BM25Manifest(
        created_at=datetime(2026, 6, 12, 1, 2, 3, 456789, tzinfo=UTC),
        db_updated_at=None,
        chunk_count=1,
    )
    record = {
        "chunk_id": 2,
        "text": "cached",
        "source_title": "B",
        "source_author": None,
        "chapter_title": None,
        "page_label": None,
    }
    write_bm25_corpus(index_path, [record], ["cached phrase"], manifest)
    config = EbookSearchConfig(rerank=RerankConfig(enabled=False), bm25_index_dir=str(index_path))

    try:
        corpus = load_bm25_corpus(config)
    finally:
        load_bm25_corpus.cache_clear()

    assert corpus.manifest == manifest
    assert corpus.records[0]["chunk_id"] == 2
    assert score_bm25_corpus("cached", corpus, limit=10)


def test_load_bm25_corpus_caches_disk_load(mocker: MockerFixture, tmp_path) -> None:
    load_bm25_corpus.cache_clear()
    manifest = BM25Manifest(created_at=datetime.now(tz=UTC), db_updated_at=None, chunk_count=1)
    record = {
        "chunk_id": 2,
        "text": "cached",
        "source_title": "B",
        "source_author": None,
        "chapter_title": None,
        "page_label": None,
        "bm25_text": "cached",
    }
    load_count = 0

    class FakeRetriever:
        """Fake persisted BM25 retriever."""

        corpus = (record,)

    class FakeBM25:
        """Fake BM25 class with observable load count."""

        @staticmethod
        def load(index_path, *, load_corpus, mmap):
            nonlocal load_count
            load_count += 1
            assert index_path == tmp_path
            assert load_corpus is True
            assert mmap is True
            return FakeRetriever()

    fake_bm25s = ModuleType("bm25s")
    fake_bm25s.BM25 = FakeBM25
    mocker.patch("python.ebook_search.bm25_corpus.read_bm25_manifest", side_effect=lambda _path: manifest)
    mocker.patch("python.ebook_search.bm25_corpus.bm25_index_exists", side_effect=lambda _path, _manifest: True)
    mocker.patch("python.ebook_search.bm25_corpus.bm25s", fake_bm25s)
    config = EbookSearchConfig(rerank=RerankConfig(enabled=False), bm25_index_dir=str(tmp_path))

    try:
        first = load_bm25_corpus(config)
        second = load_bm25_corpus(config)
    finally:
        load_bm25_corpus.cache_clear()

    assert first is second
    assert first is not None
    assert first.records == (record,)
    assert load_count == 1


def test_load_bm25_corpus_raises_when_index_is_missing(mocker: MockerFixture, tmp_path) -> None:
    load_bm25_corpus.cache_clear()
    mocker.patch("python.ebook_search.bm25_corpus.read_bm25_manifest", side_effect=lambda _path: None)
    mocker.patch("python.ebook_search.bm25_corpus.bm25_index_exists", side_effect=lambda _path, _manifest: False)
    config = EbookSearchConfig(rerank=RerankConfig(enabled=False), bm25_index_dir=str(tmp_path))

    try:
        with pytest.raises(BM25CorpusUnavailableError, match="BM25 corpus is not available"):
            load_bm25_corpus(config)
    finally:
        load_bm25_corpus.cache_clear()


def test_ensure_bm25_corpus_refreshes_missing_index(mocker: MockerFixture) -> None:
    refreshed: list[object] = []
    db_updated_at = datetime.now(tz=UTC)

    mocker.patch("python.ebook_search.bm25_corpus.read_bm25_manifest", side_effect=lambda _path: None)
    mocker.patch("python.ebook_search.bm25_corpus.bm25_index_exists", side_effect=lambda _path, _manifest: False)
    mocker.patch("python.ebook_search.bm25_corpus.corpus_last_updated_at", side_effect=lambda _session: db_updated_at)
    mocker.patch(
        "python.ebook_search.bm25_corpus.refresh_bm25_corpus",
        side_effect=lambda session, config, *, db_updated_at: refreshed.append((session, config, db_updated_at)),
    )

    config = EbookSearchConfig(rerank=RerankConfig(enabled=False))
    session = object()

    ensure_bm25_corpus(session, config)

    assert refreshed == [(session, config, db_updated_at)]


def test_ensure_bm25_corpus_refreshes_stale_index(mocker: MockerFixture) -> None:
    refreshed: list[object] = []
    created_at = datetime(2026, 1, 1, tzinfo=UTC)
    db_updated_at = datetime(2026, 1, 2, tzinfo=UTC)
    manifest = BM25Manifest(created_at=created_at, db_updated_at=created_at, chunk_count=10)

    mocker.patch("python.ebook_search.bm25_corpus.read_bm25_manifest", side_effect=lambda _path: manifest)
    mocker.patch("python.ebook_search.bm25_corpus.bm25_index_exists", side_effect=lambda _path, _manifest: True)
    mocker.patch("python.ebook_search.bm25_corpus.corpus_last_updated_at", side_effect=lambda _session: db_updated_at)
    mocker.patch(
        "python.ebook_search.bm25_corpus.refresh_bm25_corpus",
        side_effect=lambda session, config, *, db_updated_at: refreshed.append((session, config, db_updated_at)),
    )

    config = EbookSearchConfig(rerank=RerankConfig(enabled=False))
    session = object()

    ensure_bm25_corpus(session, config)

    assert refreshed == [(session, config, db_updated_at)]


def test_supported_embedding_models_match_service_names() -> None:
    assert MODEL_DIMENSIONS == {
        "qwen3-embedding-0.6b": 1024,
        "qwen3-embedding-4b": 2560,
        "qwen3-embedding-8b": 4096,
    }


def test_ensure_embedding_models_registers_service_names() -> None:
    engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
    RichieBase.metadata.create_all(engine)
    with sessionmaker(bind=engine, expire_on_commit=False, future=True)() as session:
        ensure_embedding_models(session)
        session.commit()

        models = list(session.scalars(select(EbookEmbeddingModel).order_by(EbookEmbeddingModel.name)))

    assert [(model.name, model.dimension) for model in models] == [
        ("qwen3-embedding-0.6b", 1024),
        ("qwen3-embedding-4b", 2560),
        ("qwen3-embedding-8b", 4096),
    ]


def test_1024_embedding_table_has_cosine_hnsw_index() -> None:
    indexes = {index.name: index for index in EbookChunkEmbedding1024.__table__.indexes}
    index = indexes["ix_ebook_chunk_embedding_1024_embedding_cosine"]

    assert [column.name for column in index.columns] == ["embedding"]
    assert index.dialect_options["postgresql"]["using"] == "hnsw"
    assert index.dialect_options["postgresql"]["ops"] == {"embedding": "vector_cosine_ops"}


def test_embedding_model_aliases_normalize_to_provider_names(mocker: MockerFixture) -> None:
    mocker.patch.dict(environ, {}, clear=False)

    assert normalize_embedding_model() == "qwen3-embedding-0.6b"

    environ["EBOOK_SEARCH_EMBEDDING_MODEL"] = "qwen3-embedding-0.6b"
    assert normalize_embedding_model() == "qwen3-embedding-0.6b"

    environ["EBOOK_SEARCH_EMBEDDING_MODEL"] = "Qwen3-Embedding-0.6B"
    assert normalize_embedding_model() == "qwen3-embedding-0.6b"

    environ["EBOOK_SEARCH_EMBEDDING_MODEL"] = "Qwen/Qwen3-Embedding-4B"

    assert normalize_embedding_model() == "qwen3-embedding-4b"

    environ["EBOOK_SEARCH_EMBEDDING_MODEL"] = "qwen3-embedding:8b"
    assert normalize_embedding_model() == "qwen3-embedding-8b"

    environ["EBOOK_SEARCH_EMBEDDING_MODEL"] = "qwen3-embedding-8b"
    assert normalize_embedding_model() == "qwen3-embedding-8b"


def test_answer_generation_is_enabled_by_default(mocker: MockerFixture) -> None:
    mocker.patch.dict(environ, {}, clear=False)
    environ.pop("EBOOK_SEARCH_ANSWER_ENABLED", None)

    config = load_config()

    assert config.answer_enabled is True


def test_chat_defaults_use_ollama_cloud(mocker: MockerFixture) -> None:
    mocker.patch.dict(environ, {}, clear=False)
    environ.pop("EBOOK_SEARCH_VLLM_BASE_URL", None)
    environ.pop("EBOOK_SEARCH_CHAT_MODEL", None)

    config = load_config()

    assert config.vllm_base_url == "https://ollama.com/v1"
    assert config.chat_model == "deepseek-v4-flash"


def test_chat_api_key_falls_back_to_ollama_api_key(mocker: MockerFixture) -> None:
    mocker.patch.dict(environ, {"OLLAMA_API_KEY": "ollama-key"}, clear=False)
    environ.pop("EBOOK_SEARCH_VLLM_API_KEY", None)

    config = load_config()

    assert config.vllm_api_key == "ollama-key"


def test_answer_query_does_not_call_model_when_disabled() -> None:
    config = load_config().model_copy(update={"answer_enabled": False})
    result = SearchResult(chunk_id=1, text="source text", source_title="Book")

    answer = answer_query("question", [result], config)

    assert "Answer generation is disabled" in answer