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test(test_utils.py): fix cache creation tokens

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This commit is contained in:
Krrish Dholakia 2025-09-16 19:03:16 -07:00
parent 97cc5f55d6
commit e735808614
1 changed files with 8 additions and 9 deletions
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17
tests/test_litellm/test_utils.py
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@ -508,6 +508,7 @@ def test_aaamodel_prices_and_context_window_json_is_valid():
"supports_computer_use": {"type": "boolean"},
"cache_creation_input_audio_token_cost": {"type": "number"},
"cache_creation_input_token_cost": {"type": "number"},
"cache_creation_input_token_cost_above_1hr": {"type": "number"},
"cache_creation_input_token_cost_above_200k_tokens": {"type": "number"},
"cache_read_input_token_cost": {"type": "number"},
"cache_read_input_token_cost_above_200k_tokens": {"type": "number"},
@ -661,24 +662,24 @@ def test_aaamodel_prices_and_context_window_json_is_valid():
"type": "array",
"items": {"type": "number"},
"minItems": 2,
"maxItems": 2
"maxItems": 2,
},
"input_cost_per_token": {"type": "number"},
"output_cost_per_token": {"type": "number"},
"cache_read_input_token_cost": {"type": "number"},
"output_cost_per_reasoning_token": {"type": "number"}
"output_cost_per_reasoning_token": {"type": "number"},
},
"required": ["range"],
"additionalProperties": False
}
"additionalProperties": False,
},
},
},
"additionalProperties": False,
},
}
prod_json = "./model_prices_and_context_window.json"
# prod_json = "../../model_prices_and_context_window.json"
# prod_json = "./model_prices_and_context_window.json"
prod_json = "../../model_prices_and_context_window.json"
with open(prod_json, "r") as model_prices_file:
actual_json = json.load(model_prices_file)
assert isinstance(actual_json, dict)
@ -843,7 +844,6 @@ for commitment in BEDROCK_COMMITMENTS:
print("block_list", block_list)
def test_supports_computer_use_utility():
"""
Tests the litellm.utils.supports_computer_use utility function.
@ -925,8 +925,7 @@ def test_pre_process_non_default_params(model, custom_llm_provider):
from litellm.utils import ProviderConfigManager, pre_process_non_default_params
provider_config = ProviderConfigManager.get_provider_chat_config(
model=model,
provider=LlmProviders(custom_llm_provider)
model=model, provider=LlmProviders(custom_llm_provider)
)
class ResponseFormat(BaseModel):