haiku.rag/tests/test_embedder_config.py

import pytest

from haiku.rag.config import (
    AppConfig,
    EmbeddingModelConfig,
    EmbeddingsConfig,
    OllamaConfig,
    ProvidersConfig,
)
from haiku.rag.embeddings import get_embedder


def test_ollama_embedder_uses_config():
    """Test that Ollama embedder uses the config passed to get_embedder."""
    custom_config = AppConfig(
        embeddings=EmbeddingsConfig(
            model=EmbeddingModelConfig(
                provider="ollama", name="custom-model", vector_dim=512
            ),
        ),
        providers=ProvidersConfig(
            ollama=OllamaConfig(base_url="http://custom-ollama:8080"),
        ),
    )

    embedder = get_embedder(custom_config)

    assert embedder._vector_dim == 512


def test_openai_embedder_with_base_url():
    """Test that OpenAI embedder uses custom base_url for vLLM/LM Studio."""
    custom_config = AppConfig(
        embeddings=EmbeddingsConfig(
            model=EmbeddingModelConfig(
                provider="openai",
                name="some-local-model",
                vector_dim=768,
                base_url="http://localhost:8000/v1",
            ),
        ),
    )

    embedder = get_embedder(custom_config)

    assert embedder._vector_dim == 768


def test_sentence_transformers_embedder_uses_config():
    """Test that SentenceTransformers embedder uses the config."""
    custom_config = AppConfig(
        embeddings=EmbeddingsConfig(
            model=EmbeddingModelConfig(
                provider="sentence-transformers",
                name="all-MiniLM-L6-v2",
                vector_dim=384,
            ),
        ),
    )

    embedder = get_embedder(custom_config)

    assert embedder._vector_dim == 384


def test_unsupported_provider_raises():
    """Test that unsupported provider raises ValueError."""
    custom_config = AppConfig(
        embeddings=EmbeddingsConfig(
            model=EmbeddingModelConfig(
                provider="unsupported-provider", name="model", vector_dim=512
            ),
        ),
    )

    with pytest.raises(ValueError, match="Unsupported embedding provider"):
        get_embedder(custom_config)


def test_ollama_embedder_appends_v1_when_missing():
    """Per-model base_url without /v1 should get it appended for Ollama."""
    config = AppConfig(
        embeddings=EmbeddingsConfig(
            model=EmbeddingModelConfig(
                provider="ollama",
                name="qwen3-embedding:4b",
                vector_dim=2560,
                base_url="http://my-ollama:11434",
            ),
        ),
    )
    embedder = get_embedder(config)
    pa_model = embedder._embedder._model  # type: ignore[union-attr]  # ty: ignore[unresolved-attribute]
    assert str(pa_model.base_url).rstrip("/").endswith("/v1")  # type: ignore[union-attr]  # ty: ignore[unresolved-attribute]


def test_ollama_embedder_does_not_double_append_v1():
    """If the user already includes /v1 we leave it alone."""
    config = AppConfig(
        embeddings=EmbeddingsConfig(
            model=EmbeddingModelConfig(
                provider="ollama",
                name="qwen3-embedding:4b",
                vector_dim=2560,
                base_url="http://my-ollama:11434/v1",
            ),
        ),
    )
    embedder = get_embedder(config)
    pa_model = embedder._embedder._model  # type: ignore[union-attr]  # ty: ignore[unresolved-attribute]
    url = str(pa_model.base_url).rstrip("/")  # type: ignore[union-attr]  # ty: ignore[unresolved-attribute]
    assert url.endswith("/v1")
    assert not url.endswith("/v1/v1")


def test_vllm_embedder_appends_v1_when_missing():
    """vLLM's chat-completions endpoint also lives under /v1. A user who
    forgets the suffix would otherwise POST to <host>/embeddings and get
    a 404 — match the Ollama behavior and append it."""
    config = AppConfig(
        embeddings=EmbeddingsConfig(
            model=EmbeddingModelConfig(
                provider="vllm",
                name="Qwen/Qwen3-VL-Embedding-8B",
                vector_dim=4096,
                base_url="http://my-vllm:8000",
            ),
        ),
    )
    embedder = get_embedder(config)
    base_url = embedder._base_url  # type: ignore[attr-defined]  # ty: ignore[unresolved-attribute]
    assert base_url.endswith("/v1")


def test_vllm_embedder_does_not_double_append_v1():
    """If the user already includes /v1 we leave it alone."""
    config = AppConfig(
        embeddings=EmbeddingsConfig(
            model=EmbeddingModelConfig(
                provider="vllm",
                name="Qwen/Qwen3-VL-Embedding-8B",
                vector_dim=4096,
                base_url="http://my-vllm:8000/v1",
            ),
        ),
    )
    embedder = get_embedder(config)
    base_url = embedder._base_url.rstrip("/")  # type: ignore[attr-defined]  # ty: ignore[unresolved-attribute]
    assert base_url.endswith("/v1")
    assert not base_url.endswith("/v1/v1")


def test_vector_dim_property_reports_configured_dimension():
    from haiku.rag.embeddings import EmbedderWrapper

    assert EmbedderWrapper(embedder=None, vector_dim=512).vector_dim == 512


@pytest.mark.parametrize(
    "provider,env_var",
    [("voyageai", "VOYAGE_API_KEY"), ("cohere", "CO_API_KEY")],
)
def test_saas_providers_are_wired_without_a_request(monkeypatch, provider, env_var):
    """Construction wires the SDK and reports the configured dimension."""
    monkeypatch.setenv(env_var, "test-key")
    config = AppConfig(
        embeddings=EmbeddingsConfig(
            model=EmbeddingModelConfig(
                provider=provider, name="some-model", vector_dim=1024
            ),
        ),
    )

    embedder = get_embedder(config)

    assert embedder.vector_dim == 1024
    assert embedder.supports_images is False
    # The provider and model reach the underlying pydantic-ai embedder.
    assert embedder._embedder._model == f"{provider}:some-model"  # ty: ignore[unresolved-attribute]


def test_cohere_floats_rejects_missing_embeddings():
    from types import SimpleNamespace

    from haiku.rag.embeddings.cohere import _floats

    result = SimpleNamespace(embeddings=SimpleNamespace(float_=None))

    with pytest.raises(ValueError, match="no float embeddings"):
        _floats(result)


def test_voyageai_to_pil_rejects_unsupported_type():
    from haiku.rag.embeddings.voyageai import _to_pil

    with pytest.raises(TypeError, match="Unsupported image type"):
        _to_pil("not an image")  # ty: ignore[invalid-argument-type]