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be6c5ee | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 | from concurrent.futures import ThreadPoolExecutor
import threading
from types import SimpleNamespace
import pytest
import models
def _clear_local_embedding_models():
with models._LOCAL_EMBEDDING_MODELS_LOCK:
models._LOCAL_EMBEDDING_MODELS.clear()
def test_local_embedding_preload_is_reused_with_runtime_model_config(monkeypatch):
created = []
class FakeSentenceTransformer:
def __init__(self, model, **kwargs):
created.append((model, kwargs))
monkeypatch.setattr(models, "SentenceTransformer", FakeSentenceTransformer)
_clear_local_embedding_models()
try:
preload = models.LocalSentenceTransformerWrapper(
"huggingface",
"sentence-transformers/example",
device="cpu",
model_kwargs={"revision": "stable", "trust_remote_code": False},
)
runtime_config = SimpleNamespace(name="runtime")
runtime = models.LocalSentenceTransformerWrapper(
"huggingface",
"sentence-transformers/example",
model_config=runtime_config,
model_kwargs={"trust_remote_code": False, "revision": "stable"},
device="cpu",
)
assert runtime.model is preload.model
assert runtime.a0_model_conf is runtime_config
assert created == [
(
"example",
{
"device": "cpu",
"model_kwargs": {
"revision": "stable",
"trust_remote_code": False,
},
},
)
]
finally:
_clear_local_embedding_models()
def test_local_embedding_cache_tracks_effective_constructor_options(monkeypatch):
created = []
class FakeSentenceTransformer:
def __init__(self, model, **kwargs):
created.append((model, kwargs))
monkeypatch.setattr(models, "SentenceTransformer", FakeSentenceTransformer)
_clear_local_embedding_models()
try:
first = models.LocalSentenceTransformerWrapper(
"huggingface", "sentence-transformers/example", device="cpu"
)
second = models.LocalSentenceTransformerWrapper(
"huggingface", "sentence-transformers/example", device="cuda"
)
assert second.model is not first.model
assert created == [
("example", {"device": "cpu"}),
("example", {"device": "cuda"}),
]
assert len(models._LOCAL_EMBEDDING_MODELS) == 1
finally:
_clear_local_embedding_models()
def test_concurrent_preload_and_runtime_share_one_model(monkeypatch):
created = []
construction_started = threading.Event()
release_construction = threading.Event()
class FakeSentenceTransformer:
def __init__(self, model, **kwargs):
created.append((model, kwargs))
construction_started.set()
assert release_construction.wait(timeout=2)
monkeypatch.setattr(models, "SentenceTransformer", FakeSentenceTransformer)
_clear_local_embedding_models()
try:
with ThreadPoolExecutor(max_workers=2) as executor:
first = executor.submit(
models.LocalSentenceTransformerWrapper,
"huggingface",
"sentence-transformers/example",
)
assert construction_started.wait(timeout=2)
second = executor.submit(
models.LocalSentenceTransformerWrapper,
"huggingface",
"sentence-transformers/example",
)
release_construction.set()
assert second.result().model is first.result().model
assert created == [("example", {})]
finally:
release_construction.set()
_clear_local_embedding_models()
def test_failed_model_change_keeps_the_working_cached_model(monkeypatch):
created = []
class FakeSentenceTransformer:
def __init__(self, model, **kwargs):
created.append((model, kwargs))
if model == "broken":
raise RuntimeError("model unavailable")
monkeypatch.setattr(models, "SentenceTransformer", FakeSentenceTransformer)
_clear_local_embedding_models()
try:
working = models.LocalSentenceTransformerWrapper(
"huggingface", "sentence-transformers/working"
)
with pytest.raises(RuntimeError, match="model unavailable"):
models.LocalSentenceTransformerWrapper(
"huggingface", "sentence-transformers/broken"
)
reused = models.LocalSentenceTransformerWrapper(
"huggingface", "sentence-transformers/working"
)
assert reused.model is working.model
assert created == [("working", {}), ("broken", {})]
finally:
_clear_local_embedding_models()
@pytest.mark.asyncio
async def test_preload_uses_the_runtime_embedding_configuration(monkeypatch):
import preload
from plugins._model_config.helpers import model_config
config = SimpleNamespace(
provider="huggingface",
name="sentence-transformers/example",
build_kwargs=lambda: {"device": "cpu"},
)
calls = []
embedded = []
class FakeEmbeddings:
async def aembed_query(self, text):
embedded.append(text)
def get_embedding_model(provider, name, **kwargs):
calls.append((provider, name, kwargs))
return FakeEmbeddings()
monkeypatch.setattr(
model_config, "get_embedding_model_config_object", lambda: config
)
monkeypatch.setattr(preload.models, "get_embedding_model", get_embedding_model)
await preload.preload()
assert calls == [
(
"huggingface",
"sentence-transformers/example",
{"model_config": config, "device": "cpu"},
)
]
assert embedded == ["test"]
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