"""Tests for the embedding wrapper (using the fake model fixture)."""

from __future__ import annotations

import numpy as np

from wikikb import config, embed


def test_embed_passages_shape_and_normalization(fake_model) -> None:
    vectors = embed.embed_passages(["a", "b", "c"], model=fake_model)
    assert vectors.shape == (3, config.EMBED_DIM)
    norms = np.linalg.norm(vectors, axis=1)
    assert np.allclose(norms, 1.0, atol=1e-5)


def test_embed_passages_empty(fake_model) -> None:
    vectors = embed.embed_passages([], model=fake_model)
    assert vectors.shape == (0, config.EMBED_DIM)


def test_embed_query_normalized(fake_model) -> None:
    vec = embed.embed_query("domain limit", model=fake_model)
    assert vec.shape == (config.EMBED_DIM,)
    assert np.isclose(np.linalg.norm(vec), 1.0, atol=1e-5)


def test_get_model_returns_cached(monkeypatch, fake_model) -> None:
    monkeypatch.setattr(embed, "_model", fake_model)
    assert embed.get_model() is fake_model


def test_normalize_handles_zero_vector() -> None:
    zero = np.zeros((1, config.EMBED_DIM), dtype=np.float32)
    out = embed._normalize(zero)
    assert np.all(out == 0.0)  # zero norm replaced by 1, stays zero