import pytest

from haiku.rag.config import AppConfig, Config
from haiku.rag.store.repositories.settings import ConfigMismatchError


@pytest.mark.asyncio
async def test_settings_table_populated_on_store_init(temp_db_path):
    """Test that settings table is populated with current config when store is initialized."""
    from haiku.rag.store.engine import Store
    from haiku.rag.store.repositories.settings import SettingsRepository

    async with Store(temp_db_path, create=True) as store:
        settings_repo = SettingsRepository(store)

        db_settings = await settings_repo.get_current_settings()
        config_dict = Config.model_dump(mode="json")

        # Remove version from db_settings since it's added automatically
        db_settings_without_version = {
            k: v for k, v in db_settings.items() if k != "version"
        }
        assert db_settings_without_version == config_dict


@pytest.mark.asyncio
async def test_settings_save_and_retrieve(temp_db_path):
    """Test saving and retrieving settings after config change."""
    from haiku.rag.store.engine import Store
    from haiku.rag.store.repositories.settings import SettingsRepository

    async with Store(temp_db_path, create=True) as store:
        settings_repo = SettingsRepository(store)

        original_chunk_size = Config.processing.chunk_size
        Config.processing.chunk_size = 2 * original_chunk_size

        await settings_repo.save_current_settings()
        retrieved_settings = await settings_repo.get_current_settings()
        assert retrieved_settings["processing"]["chunk_size"] == 2 * original_chunk_size

        Config.processing.chunk_size = original_chunk_size


def test_monitor_filter_patterns_config():
    """Test that monitor filter patterns are available in config."""
    assert hasattr(Config.monitor, "ignore_patterns")
    assert hasattr(Config.monitor, "include_patterns")
    assert hasattr(Config.monitor, "directories")
    assert isinstance(Config.monitor.ignore_patterns, list)
    assert isinstance(Config.monitor.include_patterns, list)
    assert isinstance(Config.monitor.directories, list)


class TestValidateConfigCompatibility:
    """Tests for validate_config_compatibility method."""

    @pytest.mark.asyncio
    async def test_empty_settings_saves_config(self, temp_db_path):
        """When settings row is missing, validation saves current config."""
        from haiku.rag.store.engine import Store
        from haiku.rag.store.repositories.settings import SettingsRepository

        async with Store(temp_db_path, create=True, skip_validation=True) as store:
            settings_repo = SettingsRepository(store)

            # Clear settings to simulate empty state
            await store.settings_table.delete("id = 'settings'")
            assert await settings_repo.get_current_settings() == {}

            # Validation should save settings
            await settings_repo.validate_config_compatibility()

            # Now settings should exist
            saved = await settings_repo.get_current_settings()
            assert (
                saved.get("embeddings", {}).get("model", {}).get("provider") is not None
            )

    @pytest.mark.asyncio
    async def test_compatible_config_no_error(self, temp_db_path):
        """Compatible config does not raise error."""
        from haiku.rag.store.engine import Store
        from haiku.rag.store.repositories.settings import SettingsRepository

        async with Store(temp_db_path, create=True) as store:
            settings_repo = SettingsRepository(store)

            # Should not raise - same config
            await settings_repo.validate_config_compatibility()

    @pytest.mark.asyncio
    async def test_provider_mismatch_raises_error(self, temp_db_path):
        """Different embedding provider raises ConfigMismatchError."""
        from haiku.rag.store.engine import Store
        from haiku.rag.store.repositories.settings import SettingsRepository

        # Create store with default config (ollama)
        async with Store(temp_db_path, create=True):
            pass

        # Create new config with different provider
        new_config = AppConfig()
        new_config.embeddings.model.provider = "openai"

        async with Store(
            temp_db_path, config=new_config, skip_validation=True
        ) as store2:
            settings_repo = SettingsRepository(store2)

            with pytest.raises(ConfigMismatchError) as exc_info:
                await settings_repo.validate_config_compatibility()

            assert "embedding provider" in str(exc_info.value)
            assert "ollama" in str(exc_info.value)
            assert "openai" in str(exc_info.value)

    @pytest.mark.asyncio
    async def test_model_mismatch_raises_error(self, temp_db_path):
        """Different embedding model raises ConfigMismatchError."""
        from haiku.rag.store.engine import Store
        from haiku.rag.store.repositories.settings import SettingsRepository

        # Create store with default config
        async with Store(temp_db_path, create=True):
            pass

        # Create new config with different model
        new_config = AppConfig()
        new_config.embeddings.model.name = "different-model"

        async with Store(
            temp_db_path, config=new_config, skip_validation=True
        ) as store2:
            settings_repo = SettingsRepository(store2)

            with pytest.raises(ConfigMismatchError) as exc_info:
                await settings_repo.validate_config_compatibility()

            assert "embedding model" in str(exc_info.value)

    @pytest.mark.asyncio
    async def test_vector_dim_mismatch_raises_error(self, temp_db_path):
        """Different vector dimension raises ConfigMismatchError."""
        from haiku.rag.store.engine import Store
        from haiku.rag.store.repositories.settings import SettingsRepository

        # Create store with default config
        async with Store(temp_db_path, create=True):
            pass

        # Create new config with different vector dimension
        new_config = AppConfig()
        new_config.embeddings.model.vector_dim = 9999

        async with Store(
            temp_db_path, config=new_config, skip_validation=True
        ) as store2:
            settings_repo = SettingsRepository(store2)

            with pytest.raises(ConfigMismatchError) as exc_info:
                await settings_repo.validate_config_compatibility()

            assert "vector dimension" in str(exc_info.value)
            assert "9999" in str(exc_info.value)