Files
basicmachines-co-basic-memory/tests/repository/test_fastembed_provider.py
2026-03-03 14:04:03 -06:00

151 lines
5.4 KiB
Python

"""Tests for FastEmbedEmbeddingProvider."""
import builtins
import sys
import pytest
from basic_memory.repository.fastembed_provider import FastEmbedEmbeddingProvider
from basic_memory.repository.semantic_errors import SemanticDependenciesMissingError
class _StubVector:
def __init__(self, values):
self._values = values
def tolist(self):
return self._values
class _StubTextEmbedding:
init_count = 0
last_init_kwargs: dict = {}
last_embed_kwargs: dict = {}
def __init__(self, model_name: str, cache_dir: str | None = None, threads: int | None = None):
self.model_name = model_name
self.embed_calls = 0
_StubTextEmbedding.last_init_kwargs = {
"model_name": model_name,
"cache_dir": cache_dir,
"threads": threads,
}
_StubTextEmbedding.init_count += 1
def embed(self, texts: list[str], batch_size: int = 64, **kwargs):
self.embed_calls += 1
_StubTextEmbedding.last_embed_kwargs = {"batch_size": batch_size, **kwargs}
for text in texts:
if "wide" in text:
yield _StubVector([1.0, 0.0, 0.0, 0.0, 0.5])
else:
yield _StubVector([1.0, 0.0, 0.0, 0.0])
@pytest.mark.asyncio
async def test_fastembed_provider_lazy_loads_and_reuses_model(monkeypatch):
"""Provider should instantiate FastEmbed lazily and reuse the loaded model."""
module = type(sys)("fastembed")
module.TextEmbedding = _StubTextEmbedding
monkeypatch.setitem(sys.modules, "fastembed", module)
_StubTextEmbedding.init_count = 0
provider = FastEmbedEmbeddingProvider(model_name="stub-model", dimensions=4)
assert provider._model is None
first = await provider.embed_query("auth query")
second = await provider.embed_documents(["database query"])
assert _StubTextEmbedding.init_count == 1
assert provider._model is not None
assert len(first) == 4
assert len(second) == 1
assert len(second[0]) == 4
@pytest.mark.asyncio
async def test_fastembed_provider_dimension_mismatch_raises_error(monkeypatch):
"""Provider should fail fast when model output dimensions differ from configured dimensions."""
module = type(sys)("fastembed")
module.TextEmbedding = _StubTextEmbedding
monkeypatch.setitem(sys.modules, "fastembed", module)
provider = FastEmbedEmbeddingProvider(model_name="stub-model", dimensions=4)
with pytest.raises(RuntimeError, match="5-dimensional vectors"):
await provider.embed_documents(["wide vector"])
@pytest.mark.asyncio
async def test_fastembed_provider_missing_dependency_raises_actionable_error(monkeypatch):
"""Missing fastembed package should raise SemanticDependenciesMissingError."""
monkeypatch.delitem(sys.modules, "fastembed", raising=False)
original_import = builtins.__import__
def _raising_import(name, globals=None, locals=None, fromlist=(), level=0):
if name == "fastembed":
raise ImportError("fastembed not installed")
return original_import(name, globals, locals, fromlist, level)
monkeypatch.setattr(builtins, "__import__", _raising_import)
provider = FastEmbedEmbeddingProvider(model_name="stub-model")
with pytest.raises(SemanticDependenciesMissingError) as error:
await provider.embed_query("test")
assert "pip install -U basic-memory" in str(error.value)
@pytest.mark.asyncio
async def test_fastembed_provider_passes_runtime_knobs_to_fastembed(monkeypatch):
"""Provider should pass optional runtime tuning knobs through to FastEmbed."""
module = type(sys)("fastembed")
module.TextEmbedding = _StubTextEmbedding
monkeypatch.setitem(sys.modules, "fastembed", module)
_StubTextEmbedding.last_init_kwargs = {}
_StubTextEmbedding.last_embed_kwargs = {}
provider = FastEmbedEmbeddingProvider(
model_name="stub-model",
dimensions=4,
batch_size=8,
cache_dir="/tmp/fastembed-cache",
threads=3,
parallel=2,
)
await provider.embed_documents(["runtime knobs"])
assert _StubTextEmbedding.last_init_kwargs == {
"model_name": "stub-model",
"cache_dir": "/tmp/fastembed-cache",
"threads": 3,
}
assert _StubTextEmbedding.last_embed_kwargs == {"batch_size": 8, "parallel": 2}
@pytest.mark.asyncio
async def test_fastembed_provider_parallel_one_disables_multiprocessing(monkeypatch):
"""parallel=1 should not pass FastEmbed multiprocessing kwargs."""
module = type(sys)("fastembed")
module.TextEmbedding = _StubTextEmbedding
monkeypatch.setitem(sys.modules, "fastembed", module)
_StubTextEmbedding.last_embed_kwargs = {}
provider = FastEmbedEmbeddingProvider(model_name="stub-model", dimensions=4, parallel=1)
await provider.embed_documents(["parallel guardrail"])
assert _StubTextEmbedding.last_embed_kwargs == {"batch_size": 64}
@pytest.mark.asyncio
async def test_fastembed_provider_parallel_two_passes_multiprocessing(monkeypatch):
"""parallel>1 should keep passing FastEmbed multiprocessing kwargs."""
module = type(sys)("fastembed")
module.TextEmbedding = _StubTextEmbedding
monkeypatch.setitem(sys.modules, "fastembed", module)
_StubTextEmbedding.last_embed_kwargs = {}
provider = FastEmbedEmbeddingProvider(model_name="stub-model", dimensions=4, parallel=2)
await provider.embed_documents(["parallel enabled"])
assert _StubTextEmbedding.last_embed_kwargs == {"batch_size": 64, "parallel": 2}