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test(cost): cover the gpt-image data_residency uplift
Added tests to validate data residency uplift for gpt-image costs.
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1 changed files with 141 additions and 1 deletions
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@ -10,6 +10,8 @@ gpt-image-1 uses token-based pricing:
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- Image Output: $40.00/1M tokens
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"""
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from typing import Final
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import pytest
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import litellm
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@ -18,6 +20,7 @@ from litellm.types.utils import (
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ImageResponse,
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ImageUsage,
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ImageUsageInputTokensDetails,
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ModelInfo,
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)
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@ -91,7 +94,6 @@ class TestGPTImageCostRouting:
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"""Test that gpt-image models are properly routed to the token-based calculator"""
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class TestGPTImage15OutputImageTokens:
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"""
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Test for GitHub issue #19508:
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@ -120,3 +122,141 @@ class TestGPTImage2OutputImageTokensNoBreakdown:
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if __name__ == "__main__":
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pytest.main([__file__, "-v"])
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class TestGPTImageDataResidencyUplift:
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"""
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Test for GitHub issue #46407:
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gpt-image cost ignored the OpenAI regional-processing (data residency) uplift.
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The chat path applies ``regional_processing_uplift_multiplier_<region>`` from
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the resolved price table inside ``generic_cost_per_token``; the image route
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never received ``data_residency``, so the uplift could never reach gpt-image
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calls. These tests pin the uplift on the image path using a price table that
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carries the multiplier key (same mechanism the chat path uses with cost-map
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entries).
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"""
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_MODEL_INFO: Final[ModelInfo] = {
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"input_cost_per_token": 5e-06,
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"output_cost_per_token": 1e-05,
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"input_cost_per_image_token": 1e-05,
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"output_cost_per_image_token": 4e-05,
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"regional_processing_uplift_multiplier_eu": 1.1,
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"regional_processing_uplift_multiplier_us": 1.1,
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}
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@staticmethod
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def _image_response() -> ImageResponse:
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return ImageResponse(
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created=1234567890,
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data=[ImageObject(url="http://example.com/image.jpg")],
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usage=ImageUsage(
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input_tokens=1000,
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input_tokens_details=ImageUsageInputTokensDetails(image_tokens=600, text_tokens=400),
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output_tokens=500,
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total_tokens=1500,
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),
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)
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def test_data_residency_uplift_applies_to_gpt_image_cost(self) -> None:
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from litellm.llms.openai.image_generation.cost_calculator import cost_calculator
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base: Final = cost_calculator(
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model="gpt-image-1",
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image_response=self._image_response(),
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custom_llm_provider="openai",
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model_info=self._MODEL_INFO,
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)
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eu: Final = cost_calculator(
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model="gpt-image-1",
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image_response=self._image_response(),
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custom_llm_provider="openai",
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model_info=self._MODEL_INFO,
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data_residency="eu",
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)
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assert base > 0
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assert abs(eu - base * 1.1) < 1e-12
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def test_data_residency_uplift_via_calculate_image_response_cost_from_usage(self) -> None:
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from litellm.litellm_core_utils.llm_cost_calc.utils import calculate_image_response_cost_from_usage
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base: Final = calculate_image_response_cost_from_usage(
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model="gpt-image-1",
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image_response=self._image_response(),
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custom_llm_provider="openai",
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model_info=self._MODEL_INFO,
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)
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eu: Final = calculate_image_response_cost_from_usage(
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model="gpt-image-1",
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image_response=self._image_response(),
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custom_llm_provider="openai",
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model_info=self._MODEL_INFO,
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data_residency="eu",
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)
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assert base is not None and eu is not None
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assert abs(eu - base * 1.1) < 1e-12
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def test_no_uplift_when_model_carries_no_multiplier(self) -> None:
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from litellm.llms.openai.image_generation.cost_calculator import cost_calculator
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model_info: Final[ModelInfo] = {
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"input_cost_per_token": 5e-06,
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"output_cost_per_token": 1e-05,
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"input_cost_per_image_token": 1e-05,
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"output_cost_per_image_token": 4e-05,
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}
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base: Final = cost_calculator(
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model="gpt-image-1",
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image_response=self._image_response(),
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custom_llm_provider="openai",
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model_info=model_info,
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)
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eu: Final = cost_calculator(
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model="gpt-image-1",
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image_response=self._image_response(),
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custom_llm_provider="openai",
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model_info=model_info,
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data_residency="eu",
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)
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assert eu == base
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def test_no_uplift_when_data_residency_absent(self) -> None:
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from litellm.llms.openai.image_generation.cost_calculator import cost_calculator
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none_region: Final = cost_calculator(
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model="gpt-image-1",
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image_response=self._image_response(),
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custom_llm_provider="openai",
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model_info=self._MODEL_INFO,
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data_residency=None,
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)
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base: Final = cost_calculator(
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model="gpt-image-1",
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image_response=self._image_response(),
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custom_llm_provider="openai",
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model_info=self._MODEL_INFO,
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)
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assert none_region == base
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def test_completion_cost_threads_data_residency_to_image_route(self, monkeypatch: pytest.MonkeyPatch) -> None:
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"""End-to-end: completion_cost's image branch must hand data_residency to the route."""
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from litellm.cost_calculator import completion_cost
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monkeypatch.setitem(litellm.model_cost["gpt-image-1"], "regional_processing_uplift_multiplier_eu", 1.1)
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base: Final = completion_cost(
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completion_response=self._image_response(),
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model="gpt-image-1",
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custom_llm_provider="openai",
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call_type="image_generation",
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)
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eu: Final = completion_cost(
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completion_response=self._image_response(),
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model="gpt-image-1",
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custom_llm_provider="openai",
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call_type="image_generation",
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data_residency="eu",
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)
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assert base > 0
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assert abs(eu - base * 1.1) < 1e-12
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