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test(model_prices): update data residency tests to use gpt-5.4 as the uplift model

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The tests were using gpt-5 which no longer carries the regional processing
uplift after correcting which models have it. Switch to gpt-5.4 (released
2026-03-05, the cutoff date) and add a regression parametrize covering
all pre-cutoff models to pin that they stay uplift-free.
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mgalbato 2026-06-23 16:38:35 -04:00
parent 8900535d7c
commit 0f15f7857f
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1 changed files with 26 additions and 8 deletions
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34
tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
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@ -1499,19 +1499,20 @@ def _local_model_cost_map():
@pytest.mark.parametrize("data_residency", ["eu", "us"])
def test_data_residency_applies_uplift(data_residency, _local_model_cost_map):
"""gpt-5 should apply the regional processing uplift multiplier when
data_residency is set."""
"""gpt-5.4 should apply the regional processing uplift multiplier when
data_residency is set. gpt-5.4+ (released 2026-03-05) carry the 10% uplift;
gpt-5 and older models do not."""
from litellm.types.utils import Usage
usage = Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500)
base = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
)
regional = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
data_residency=data_residency,
@ -1526,6 +1527,23 @@ def test_data_residency_applies_uplift(data_residency, _local_model_cost_map):
assert regional[1] == pytest.approx(base[1] * 1.10, rel=1e-9)
@pytest.mark.parametrize("model", ["gpt-5", "gpt-5-mini", "gpt-5-nano", "gpt-5-pro", "gpt-4o", "gpt-4.1"])
def test_data_residency_no_uplift_for_pre_march_2026_models(model, _local_model_cost_map):
"""Models released before 2026-03-05 must not have the regional uplift."""
from litellm.types.utils import Usage
usage = Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500)
base = generic_cost_per_token(model=model, usage=usage, custom_llm_provider="openai")
regional = generic_cost_per_token(
model=model, usage=usage, custom_llm_provider="openai", data_residency="eu"
)
assert base == regional, (
f"{model} should not have a regional uplift, but cost changed with data_residency"
)
def test_data_residency_no_uplift_for_unmarked_model(_local_model_cost_map):
"""A model without a regional_processing_uplift_multiplier_* entry should
fall back to base pricing, not error."""
@ -1555,12 +1573,12 @@ def test_data_residency_none_no_uplift(_local_model_cost_map):
usage = Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500)
base = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
)
explicit_none = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
data_residency=None,
@ -1576,13 +1594,13 @@ def test_data_residency_composes_with_service_tier(_local_model_cost_map):
usage = Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500)
priority_base = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
service_tier="priority",
)
priority_eu = generic_cost_per_token(
model="gpt-5",
model="gpt-5.4",
usage=usage,
custom_llm_provider="openai",
service_tier="priority",