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import sys, os |
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import traceback |
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sys.path.insert( |
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0, os.path.abspath("../..") |
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) |
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import time |
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import litellm |
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from litellm import get_max_tokens, model_cost, open_ai_chat_completion_models |
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import pytest |
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def test_get_gpt3_tokens(): |
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max_tokens = get_max_tokens("gpt-3.5-turbo") |
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print(max_tokens) |
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assert max_tokens == 4097 |
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def test_get_palm_tokens(): |
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max_tokens = get_max_tokens("palm/chat-bison") |
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assert max_tokens == 4096 |
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print(max_tokens) |
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def test_zephyr_hf_tokens(): |
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max_tokens = get_max_tokens("huggingface/HuggingFaceH4/zephyr-7b-beta") |
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print(max_tokens) |
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assert max_tokens == 32768 |
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def test_cost_ft_gpt_35(): |
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try: |
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from litellm import ModelResponse, Choices, Message |
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from litellm.utils import Usage |
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resp = ModelResponse( |
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id="chatcmpl-e41836bb-bb8b-4df2-8e70-8f3e160155ac", |
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choices=[ |
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Choices( |
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finish_reason=None, |
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index=0, |
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message=Message( |
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content=" Sure! Here is a short poem about the sky:\n\nA canvas of blue, a", |
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role="assistant", |
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), |
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) |
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], |
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created=1700775391, |
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model="ft:gpt-3.5-turbo:my-org:custom_suffix:id", |
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object="chat.completion", |
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system_fingerprint=None, |
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usage=Usage(prompt_tokens=21, completion_tokens=17, total_tokens=38), |
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) |
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cost = litellm.completion_cost(completion_response=resp) |
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print("\n Calculated Cost for ft:gpt-3.5", cost) |
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input_cost = model_cost["ft:gpt-3.5-turbo"]["input_cost_per_token"] |
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output_cost = model_cost["ft:gpt-3.5-turbo"]["output_cost_per_token"] |
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print(input_cost, output_cost) |
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expected_cost = (input_cost * resp.usage.prompt_tokens) + ( |
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output_cost * resp.usage.completion_tokens |
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) |
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print("\n Excpected cost", expected_cost) |
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assert cost == expected_cost |
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except Exception as e: |
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pytest.fail( |
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f"Cost Calc failed for ft:gpt-3.5. Expected {expected_cost}, Calculated cost {cost}" |
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) |
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def test_cost_azure_gpt_35(): |
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try: |
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from litellm import ModelResponse, Choices, Message |
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from litellm.utils import Usage |
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resp = ModelResponse( |
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id="chatcmpl-e41836bb-bb8b-4df2-8e70-8f3e160155ac", |
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choices=[ |
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Choices( |
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finish_reason=None, |
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index=0, |
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message=Message( |
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content=" Sure! Here is a short poem about the sky:\n\nA canvas of blue, a", |
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role="assistant", |
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), |
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) |
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], |
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model="gpt-35-turbo", |
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usage=Usage(prompt_tokens=21, completion_tokens=17, total_tokens=38), |
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) |
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cost = litellm.completion_cost( |
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completion_response=resp, model="azure/gpt-35-turbo" |
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) |
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print("\n Calculated Cost for azure/gpt-3.5-turbo", cost) |
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input_cost = model_cost["azure/gpt-35-turbo"]["input_cost_per_token"] |
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output_cost = model_cost["azure/gpt-35-turbo"]["output_cost_per_token"] |
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expected_cost = (input_cost * resp.usage.prompt_tokens) + ( |
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output_cost * resp.usage.completion_tokens |
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) |
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print("\n Excpected cost", expected_cost) |
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assert cost == expected_cost |
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except Exception as e: |
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pytest.fail( |
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f"Cost Calc failed for azure/gpt-3.5-turbo. Expected {expected_cost}, Calculated cost {cost}" |
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) |
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test_cost_azure_gpt_35() |
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def test_cost_azure_embedding(): |
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try: |
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import asyncio |
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litellm.set_verbose = True |
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async def _test(): |
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response = await litellm.aembedding( |
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model="azure/azure-embedding-model", |
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input=["good morning from litellm", "gm"], |
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) |
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print(response) |
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return response |
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response = asyncio.run(_test()) |
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cost = litellm.completion_cost(completion_response=response) |
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print("Cost", cost) |
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expected_cost = float("7e-07") |
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assert cost == expected_cost |
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except Exception as e: |
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pytest.fail( |
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f"Cost Calc failed for azure/gpt-3.5-turbo. Expected {expected_cost}, Calculated cost {cost}" |
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) |
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