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test(cost): scope image generation tool cost tests to the new cases
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This commit is contained in:
Devin AI
parent
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commit
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1 changed files with 83 additions and 40 deletions
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@ -1,3 +1,4 @@
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import pytest
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import litellm
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@ -16,7 +17,9 @@ def test_web_search_cost_low():
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web_search_options=web_search_options, model_info=model_info
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)
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assert cost == model_info["search_context_cost_per_query"]["search_context_size_low"]
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assert (
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cost == model_info["search_context_cost_per_query"]["search_context_size_low"]
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)
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def test_web_search_cost_medium():
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@ -27,7 +30,10 @@ def test_web_search_cost_medium():
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web_search_options=web_search_options, model_info=model_info
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)
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assert cost == model_info["search_context_cost_per_query"]["search_context_size_medium"]
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assert (
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cost
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== model_info["search_context_cost_per_query"]["search_context_size_medium"]
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)
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def test_web_search_cost_high():
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@ -38,21 +44,33 @@ def test_web_search_cost_high():
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web_search_options=web_search_options, model_info=model_info
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)
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assert cost == model_info["search_context_cost_per_query"]["search_context_size_high"]
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assert (
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cost == model_info["search_context_cost_per_query"]["search_context_size_high"]
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)
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# Test file search cost calculation
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def test_file_search_cost():
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file_search = FileSearchTool(type="file_search")
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cost = StandardBuiltInToolCostTracking.get_cost_for_file_search(file_search=file_search)
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cost = StandardBuiltInToolCostTracking.get_cost_for_file_search(
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file_search=file_search
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)
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assert cost == 0.0025 # $2.50/1000 calls = 0.0025 per call
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# Test edge cases
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def test_none_inputs():
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# Test with None inputs
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assert StandardBuiltInToolCostTracking.get_cost_for_web_search(web_search_options=None, model_info=None) == 0.0
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assert StandardBuiltInToolCostTracking.get_cost_for_file_search(file_search=None) == 0.0
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assert (
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StandardBuiltInToolCostTracking.get_cost_for_web_search(
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web_search_options=None, model_info=None
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)
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== 0.0
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)
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assert (
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StandardBuiltInToolCostTracking.get_cost_for_file_search(file_search=None)
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== 0.0
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)
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# Test the main get_cost_for_built_in_tools method
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@ -77,7 +95,9 @@ def test_get_cost_for_built_in_tools_file_search():
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Test that the cost for a file search is 0.00 when no response object is provided
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"""
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model = "gpt-4"
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standard_built_in_tools_params = StandardBuiltInToolsParams(file_search=FileSearchTool(type="file_search"))
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standard_built_in_tools_params = StandardBuiltInToolsParams(
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file_search=FileSearchTool(type="file_search")
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)
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cost = StandardBuiltInToolCostTracking.get_cost_for_built_in_tools(
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model=model,
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@ -120,7 +140,9 @@ def test_get_cost_for_anthropic_web_search_with_server_tool_use_dict():
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usage = Usage(server_tool_use={"web_search_requests": 1})
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assert isinstance(usage.server_tool_use, ServerToolUse)
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assert StandardBuiltInToolCostTracking.response_object_includes_web_search_call(response_object=None, usage=usage)
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assert StandardBuiltInToolCostTracking.response_object_includes_web_search_call(
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response_object=None, usage=usage
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)
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def test_anthropic_web_search_cost_from_raw_response_dict_when_usage_drops_server_tool_use():
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@ -159,7 +181,9 @@ def test_anthropic_web_search_cost_from_raw_response_dict_when_usage_drops_serve
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standard_built_in_tools_params=None,
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)
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per_query_cost = litellm.get_model_info(model)["search_context_cost_per_query"]["search_context_size_medium"]
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per_query_cost = litellm.get_model_info(model)["search_context_cost_per_query"][
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"search_context_size_medium"
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]
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assert cost == per_query_cost * web_search_requests
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assert cost > 0.0
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assert getattr(usage, "server_tool_use", None) is None
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@ -197,7 +221,9 @@ def test_anthropic_web_search_cost_from_raw_response_dict_when_usage_is_none():
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standard_built_in_tools_params=None,
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)
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per_query_cost = litellm.get_model_info(model)["search_context_cost_per_query"]["search_context_size_medium"]
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per_query_cost = litellm.get_model_info(model)["search_context_cost_per_query"][
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"search_context_size_medium"
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]
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assert cost == per_query_cost * web_search_requests
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@ -261,14 +287,18 @@ def test_anthropic_response_usage_block_preserves_server_tool_use():
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assert dumped_usage["server_tool_use"] == {"web_search_requests": 2}
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@pytest.mark.parametrize("model", ["gemini/gemini-2.0-flash-001", "gemini-2.0-flash-001"])
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@pytest.mark.parametrize(
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"model", ["gemini/gemini-2.0-flash-001", "gemini-2.0-flash-001"]
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)
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def test_get_cost_for_gemini_web_search(model):
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"""
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Test that the cost for a web search is 0.00 when no response object is provided
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"""
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from litellm.types.utils import PromptTokensDetailsWrapper, Usage
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usage = Usage(prompt_tokens_details=PromptTokensDetailsWrapper(web_search_requests=1))
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usage = Usage(
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prompt_tokens_details=PromptTokensDetailsWrapper(web_search_requests=1)
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)
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cost = StandardBuiltInToolCostTracking.get_cost_for_built_in_tools(
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model=model,
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usage=usage,
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@ -326,7 +356,9 @@ def test_completion_cost_includes_web_search_without_standard_built_in_tools_par
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)
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assert web_search_cost > 0, "Web search cost should be non-zero"
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assert cost >= web_search_cost, f"completion_cost ({cost}) should include web search cost ({web_search_cost})"
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assert (
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cost >= web_search_cost
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), f"completion_cost ({cost}) should include web search cost ({web_search_cost})"
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@pytest.mark.parametrize(
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@ -353,14 +385,18 @@ def test_gemini_3x_web_search_billed_per_query(model, local_model_cost_map):
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web_search_requests = 2
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model_info = litellm.get_model_info(model)
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assert model_info["web_search_billing_unit"] == "per_query"
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per_query_cost = model_info["search_context_cost_per_query"]["search_context_size_medium"]
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per_query_cost = model_info["search_context_cost_per_query"][
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"search_context_size_medium"
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]
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expected_cost = per_query_cost * web_search_requests
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usage = Usage(
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prompt_tokens=11,
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completion_tokens=100,
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total_tokens=111,
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prompt_tokens_details=PromptTokensDetailsWrapper(text_tokens=11, web_search_requests=web_search_requests),
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prompt_tokens_details=PromptTokensDetailsWrapper(
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text_tokens=11, web_search_requests=web_search_requests
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),
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)
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cost = StandardBuiltInToolCostTracking.get_cost_for_built_in_tools(
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@ -372,7 +408,8 @@ def test_gemini_3x_web_search_billed_per_query(model, local_model_cost_map):
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)
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assert cost == pytest.approx(expected_cost), (
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f"Expected {web_search_requests} x ${per_query_cost} = ${expected_cost} per_query search fee, got ${cost}"
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f"Expected {web_search_requests} x ${per_query_cost} = ${expected_cost} "
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f"per_query search fee, got ${cost}"
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)
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@ -415,13 +452,17 @@ def test_gemini_2x_web_search_still_billed_per_prompt(local_model_cost_map):
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model = "vertex_ai/gemini-2.5-flash"
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model_info = litellm.get_model_info(model)
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assert not model_info.get("web_search_billing_unit")
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expected_cost = model_info["search_context_cost_per_query"]["search_context_size_medium"]
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expected_cost = model_info["search_context_cost_per_query"][
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"search_context_size_medium"
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]
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usage = Usage(
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prompt_tokens=11,
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completion_tokens=100,
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total_tokens=111,
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prompt_tokens_details=PromptTokensDetailsWrapper(text_tokens=11, web_search_requests=2),
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prompt_tokens_details=PromptTokensDetailsWrapper(
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text_tokens=11, web_search_requests=2
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),
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)
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cost = StandardBuiltInToolCostTracking.get_cost_for_built_in_tools(
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@ -433,7 +474,8 @@ def test_gemini_2x_web_search_still_billed_per_prompt(local_model_cost_map):
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)
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assert cost == pytest.approx(expected_cost), (
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f"Expected flat ${expected_cost} per_prompt search fee (2 queries clamped to 1), got ${cost}"
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f"Expected flat ${expected_cost} per_prompt search fee (2 queries clamped to 1), "
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f"got ${cost}"
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)
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@ -459,7 +501,9 @@ def test_web_search_provider_prefix_fallback_does_not_misprice_non_gemini_model(
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prompt_tokens=11,
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completion_tokens=100,
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total_tokens=111,
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prompt_tokens_details=PromptTokensDetailsWrapper(text_tokens=11, web_search_requests=2),
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prompt_tokens_details=PromptTokensDetailsWrapper(
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text_tokens=11, web_search_requests=2
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),
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)
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cost = StandardBuiltInToolCostTracking.get_cost_for_built_in_tools(
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@ -482,6 +526,7 @@ def _openai_responses_with_web_search_calls(model, num_calls):
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ResponseFunctionWebSearch,
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)
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output = [
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ResponseFunctionWebSearch(
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id=f"ws_{i}",
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@ -512,7 +557,9 @@ def test_openai_responses_web_search_multiplied_by_call_count(local_model_cost_m
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from litellm.types.utils import Usage
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model = "gpt-4o-search-preview"
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per_call = litellm.get_model_info(model)["search_context_cost_per_query"]["search_context_size_medium"]
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per_call = litellm.get_model_info(model)["search_context_cost_per_query"][
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"search_context_size_medium"
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]
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usage = Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15)
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for num_calls in (1, 3):
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@ -539,7 +586,9 @@ def test_web_search_call_count_reads_dict_output_items(local_model_cost_map):
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from litellm.types.utils import Usage
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model = "gpt-4o-search-preview"
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per_call = litellm.get_model_info(model)["search_context_cost_per_query"]["search_context_size_medium"]
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per_call = litellm.get_model_info(model)["search_context_cost_per_query"][
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"search_context_size_medium"
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]
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response = ResponsesAPIResponse.model_validate(
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{
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@ -548,7 +597,10 @@ def test_web_search_call_count_reads_dict_output_items(local_model_cost_map):
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"model": model,
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"object": "response",
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"status": "completed",
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"output": [{"type": "web_search_call", "id": f"ws_{i}", "status": "completed"} for i in range(3)],
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"output": [
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{"type": "web_search_call", "id": f"ws_{i}", "status": "completed"}
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for i in range(3)
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],
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}
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)
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assert all(isinstance(item, dict) for item in response.output)
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@ -561,7 +613,9 @@ def test_web_search_call_count_reads_dict_output_items(local_model_cost_map):
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standard_built_in_tools_params=None,
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)
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assert cost == pytest.approx(3 * per_call), f"3 dict-shaped web searches must bill 3 x ${per_call}, got ${cost}"
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assert cost == pytest.approx(3 * per_call), (
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f"3 dict-shaped web searches must bill 3 x ${per_call}, got ${cost}"
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)
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# Note: File search integration test removed due to complex annotation detection logic
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@ -641,6 +695,8 @@ _BEDROCK_MANTLE_WEB_SEARCH_MODELS = (
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_BEDROCK_MANTLE_WEB_SEARCH_RATE = 0.012
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def _openai_responses_response(model, output):
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return ResponsesAPIResponse.model_validate(
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{
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@ -667,12 +723,7 @@ _GPT_IMAGE_1_HIGH_1024_COST_KEY = "high/1024-x-1024/gpt-image-1"
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def test_responses_image_generation_call_billed_as_tool_usage_cost(local_model_cost_map):
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"""
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Regression: a Responses API output carrying an image_generation_call item was
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charged $0 of tool usage because get_cost_for_built_in_tools only looked for
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web/file search calls. A completed image_generation_call must be billed at the
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gpt-image-1 rate for its reported quality and size.
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"""
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"""A completed image_generation_call in the Responses output bills at the gpt-image-1 rate for its quality/size."""
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expected_image_cost = litellm.model_cost[_GPT_IMAGE_1_HIGH_1024_COST_KEY]["input_cost_per_image"]
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response = _openai_responses_response(
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"gpt-5",
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@ -702,11 +753,7 @@ def test_responses_image_generation_call_billed_as_tool_usage_cost(local_model_c
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def test_responses_web_search_and_image_generation_costs_are_additive(local_model_cost_map):
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"""
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Regression: get_cost_for_built_in_tools returned early after the web search
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branch, so a response billed for web search never reached image generation
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pricing. A response with both must bill both.
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"""
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"""A response billed for web search must still also bill its image_generation_call items."""
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model = "gpt-4o-search-preview"
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image_cost = litellm.model_cost[_GPT_IMAGE_1_HIGH_1024_COST_KEY]["input_cost_per_image"]
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image_item = {
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@ -775,11 +822,7 @@ def test_responses_incomplete_image_generation_call_not_billed(local_model_cost_
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def test_completion_cost_includes_responses_image_generation_tool_cost(local_model_cost_map):
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"""
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An image_generation_call in the Responses output must flow through
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completion_cost: the billed total for the same response without the image
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item is the token-only baseline the image item must exceed by its tool cost.
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"""
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"""The image tool fee must flow through completion_cost on top of the token-only baseline."""
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image_item = {
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"type": "image_generation_call",
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"id": "ig_1",
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