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import sys, os
import traceback
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
import time
import litellm
from litellm import get_max_tokens, model_cost, open_ai_chat_completion_models
import pytest
def test_get_gpt3_tokens():
max_tokens = get_max_tokens("gpt-3.5-turbo")
print(max_tokens)
assert max_tokens==4097
# print(results)
test_get_gpt3_tokens()
def test_get_palm_tokens():
# # 🦄🦄🦄🦄🦄🦄🦄🦄
max_tokens = get_max_tokens("palm/chat-bison")
assert max_tokens == 4096
print(max_tokens)
test_get_palm_tokens()
def test_zephyr_hf_tokens():
max_tokens = get_max_tokens("huggingface/HuggingFaceH4/zephyr-7b-beta")
print(max_tokens)
assert max_tokens == 32768
test_zephyr_hf_tokens()
def test_cost_ft_gpt_35():
try:
# this tests if litellm.completion_cost can calculate cost for ft:gpt-3.5-turbo:my-org:custom_suffix:id
# it needs to lookup ft:gpt-3.5-turbo in the litellm model_cost map to get the correct cost
from litellm import ModelResponse, Choices, Message
from litellm.utils import Usage
resp = ModelResponse(
id='chatcmpl-e41836bb-bb8b-4df2-8e70-8f3e160155ac',
choices=[Choices(finish_reason=None, index=0,
message=Message(content=' Sure! Here is a short poem about the sky:\n\nA canvas of blue, a', role='assistant'))],
created=1700775391,
model='ft:gpt-3.5-turbo:my-org:custom_suffix:id',
object='chat.completion', system_fingerprint=None,
usage=Usage(prompt_tokens=21, completion_tokens=17, total_tokens=38)
)
cost = litellm.completion_cost(completion_response=resp)
print("\n Calculated Cost for ft:gpt-3.5", cost)
input_cost = model_cost["ft:gpt-3.5-turbo"]["input_cost_per_token"]
output_cost = model_cost["ft:gpt-3.5-turbo"]["output_cost_per_token"]
print(input_cost, output_cost)
expected_cost = (input_cost*resp.usage.prompt_tokens) + (output_cost*resp.usage.completion_tokens)
print("\n Excpected cost", expected_cost)
assert cost == expected_cost
except Exception as e:
pytest.fail(f"Cost Calc failed for ft:gpt-3.5. Expected {expected_cost}, Calculated cost {cost}")
test_cost_ft_gpt_35()
def test_cost_azure_gpt_35():
try:
# this tests if litellm.completion_cost can calculate cost for azure/chatgpt-deployment-2 which maps to azure/gpt-3.5-turbo
# for this test we check if passing `model` to completion_cost overrides the completion cost
from litellm import ModelResponse, Choices, Message
from litellm.utils import Usage
resp = ModelResponse(
id='chatcmpl-e41836bb-bb8b-4df2-8e70-8f3e160155ac',
choices=[Choices(finish_reason=None, index=0,
message=Message(content=' Sure! Here is a short poem about the sky:\n\nA canvas of blue, a', role='assistant'))],
model='azure/gpt-35-turbo', # azure always has model written like this
usage=Usage(prompt_tokens=21, completion_tokens=17, total_tokens=38)
)
cost = litellm.completion_cost(completion_response=resp, model="azure/gpt-3.5-turbo")
print("\n Calculated Cost for azure/gpt-3.5-turbo", cost)
input_cost = model_cost["azure/gpt-3.5-turbo"]["input_cost_per_token"]
output_cost = model_cost["azure/gpt-3.5-turbo"]["output_cost_per_token"]
expected_cost = (input_cost*resp.usage.prompt_tokens) + (output_cost*resp.usage.completion_tokens)
print("\n Excpected cost", expected_cost)
assert cost == expected_cost
except Exception as e:
pytest.fail(f"Cost Calc failed for azure/gpt-3.5-turbo. Expected {expected_cost}, Calculated cost {cost}")
test_cost_azure_gpt_35()
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