phoenix/litellm-mirror
0
0
Fork 1
mirror of https://github.com/BerriAI/litellm.git synced 2025-04-26 11:14:04 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

test(utils.py): handle scenario where text tokens + reasoning tokens … (#10165)

Browse source 
* test(utils.py): handle scenario where text tokens + reasoning tokens set, but reasoning tokens not charged separately

Addresses https://github.com/BerriAI/litellm/pull/10141#discussion_r2051555332

* fix(vertex_and_google_ai_studio.py): only set content if non-empty str
This commit is contained in:
Krish Dholakia 2025-04-19 12:32:38 -07:00 • committed by GitHub
parent 99db1b7690
commit 03b5399f86
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
5 changed files with 90 additions and 49 deletions
Download patch file Download diff file Expand all files Collapse all files

41
tests/litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
View file

@ -26,6 +26,47 @@ from litellm.litellm_core_utils.llm_cost_calc.utils import generic_cost_per_toke
from litellm.types.utils import Usage
def test_reasoning_tokens_no_price_set():
model = "o1-mini"
custom_llm_provider = "openai"
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
litellm.model_cost = litellm.get_model_cost_map(url="")
model_cost_map = litellm.model_cost[model]
usage = Usage(
completion_tokens=1578,
prompt_tokens=17,
total_tokens=1595,
completion_tokens_details=CompletionTokensDetailsWrapper(
accepted_prediction_tokens=None,
audio_tokens=None,
reasoning_tokens=952,
rejected_prediction_tokens=None,
text_tokens=626,
),
prompt_tokens_details=PromptTokensDetailsWrapper(
audio_tokens=None, cached_tokens=None, text_tokens=17, image_tokens=None
),
)
prompt_cost, completion_cost = generic_cost_per_token(
model=model,
usage=usage,
custom_llm_provider="openai",
)
assert round(prompt_cost, 10) == round(
model_cost_map["input_cost_per_token"] * usage.prompt_tokens,
10,
)
print(f"completion_cost: {completion_cost}")
expected_completion_cost = (
model_cost_map["output_cost_per_token"] * usage.completion_tokens
)
print(f"expected_completion_cost: {expected_completion_cost}")
assert round(completion_cost, 10) == round(
expected_completion_cost,
10,
)
def test_reasoning_tokens_gemini():
model = "gemini-2.5-flash-preview-04-17"
custom_llm_provider = "gemini"