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test(utils): exercise embedding drop params in CI

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Signed-off-by: Hasnaat Hussain <hasnaat.hussain.2@gmail.com>
This commit is contained in:
Hasnaat Hussain 2026-08-12 23:58:52 +05:00
parent 6b2a5e7deb
commit 32fe2cb73c
2 changed files with 32 additions and 32 deletions
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32
tests/llm_translation/test_optional_params.py
View file

@ -1120,38 +1120,6 @@ def test_lm_studio_embedding_params():
assert len(optional_params) == 0
@pytest.mark.parametrize("provider", ["azure", "together_ai"])
def test_embedding_dimensions_drop_params_for_openai_compatible_provider(provider):
previous_drop_params = litellm.drop_params
try:
litellm.drop_params = False
dropped = get_optional_params_embeddings(
model=f"{provider}/dummy-model",
custom_llm_provider=provider,
dimensions=512,
drop_params=True,
)
assert "dimensions" not in dropped
litellm.drop_params = True
dropped_globally = get_optional_params_embeddings(
model=f"{provider}/dummy-model",
custom_llm_provider=provider,
dimensions=512,
)
assert "dimensions" not in dropped_globally
litellm.drop_params = False
preserved = get_optional_params_embeddings(
model=f"{provider}/dummy-model",
custom_llm_provider=provider,
dimensions=512,
)
assert preserved["dimensions"] == 512
finally:
litellm.drop_params = previous_drop_params
def test_ollama_pydantic_obj():
from pydantic import BaseModel

32
tests/test_litellm/test_utils.py
View file

@ -733,6 +733,38 @@ def test_cohere_embedding_optional_params():
assert optional_params is not None
@pytest.mark.parametrize("provider", ["azure", "together_ai"])
def test_embedding_dimensions_drop_params_for_openai_compatible_provider(provider):
previous_drop_params = litellm.drop_params
try:
litellm.drop_params = False
dropped = litellm.utils.get_optional_params_embeddings(
model=f"{provider}/dummy-model",
custom_llm_provider=provider,
dimensions=512,
drop_params=True,
)
assert "dimensions" not in dropped
litellm.drop_params = True
dropped_globally = litellm.utils.get_optional_params_embeddings(
model=f"{provider}/dummy-model",
custom_llm_provider=provider,
dimensions=512,
)
assert "dimensions" not in dropped_globally
litellm.drop_params = False
preserved = litellm.utils.get_optional_params_embeddings(
model=f"{provider}/dummy-model",
custom_llm_provider=provider,
dimensions=512,
)
assert preserved["dimensions"] == 512
finally:
litellm.drop_params = previous_drop_params
def validate_model_cost_values(model_data, exceptions=None):
"""
Validates that cost values in model data do not exceed 1.