"""嵌入模型测试."""
import pytest

from src.core.config import EmbedConfig
from src.core.embedder import LocalEmbedder, APIEmbedder, create_embedder, batch_embed


class TestLocalEmbedder:
    """本地嵌入器测试."""

    @pytest.fixture
    def local_config(self):
        return EmbedConfig(mode="local")

    def test_create_local_embedder(self, local_config):
        """创建本地嵌入器，验证维度正确."""
        embedder = create_embedder(local_config)
        assert embedder.dimension > 0
        assert isinstance(embedder.dimension, int)
        assert isinstance(embedder, LocalEmbedder)

    def test_embed_single_text(self, local_config):
        """嵌入单条文本返回正确维度向量."""
        embedder = create_embedder(local_config)
        result = embedder.embed(["你好世界"])
        assert len(result) == 1
        assert len(result[0]) == embedder.dimension
        assert all(isinstance(v, float) for v in result[0])

    def test_embed_multiple_texts(self, local_config):
        """嵌入多条文本返回对应数量的向量."""
        embedder = create_embedder(local_config)
        texts = ["第一段文本", "第二段文本", "第三段文本"]
        result = embedder.embed(texts)
        assert len(result) == 3
        for vec in result:
            assert len(vec) == embedder.dimension

    def test_embed_empty_list_raises(self, local_config):
        """空列表应抛出异常."""
        embedder = create_embedder(local_config)
        with pytest.raises(ValueError):
            embedder.embed([])


class TestAPIEmbedder:
    """API 嵌入器测试."""

    def test_api_embedder_init(self):
        """API 嵌入器初始化."""
        cfg = EmbedConfig(mode="api", api_base="https://api.test.com", api_key="sk-test")
        emb = APIEmbedder(cfg)
        assert emb.dimension == 1536

    def test_api_embedder_empty_raises(self):
        """API 嵌入器空列表抛异常."""
        cfg = EmbedConfig(mode="api")
        emb = APIEmbedder(cfg)
        with pytest.raises(ValueError):
            emb.embed([])


class TestBatchEmbed:
    """分批嵌入测试."""

    def test_batch_embed(self):
        """分批嵌入返回正确数量."""
        embedder = create_embedder(EmbedConfig(mode="local"))
        texts = ["测试文本"] * 70  # 超过 batch_size 32
        results = batch_embed(embedder, texts, batch_size=32)
        assert len(results) == 70
        assert len(results[0]) == embedder.dimension