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https://github.com/BerriAI/litellm.git
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1105e35538
* fix(o_series_transformation.py): add 'reasoning_effort' as o series model param Closes https://github.com/BerriAI/litellm/issues/8182 * fix(main.py): ensure `reasoning_effort` is a mapped openai param * refactor(azure/): rename o1_[x] files to o_series_[x] * refactor(base_llm_unit_tests.py): refactor testing for o series reasoning effort * test(test_azure_o_series.py): have azure o series tests correctly inherit from base o series model tests * feat(base_utils.py): support translating 'developer' role to 'system' role for non-openai providers Makes it easy to switch from openai to anthropic * fix: fix linting errors * fix(base_llm_unit_tests.py): fix test * fix(main.py): add missing param
61 lines
1.7 KiB
Python
61 lines
1.7 KiB
Python
import pytest
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from litellm import acompletion
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from litellm import completion
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def test_acompletion_params():
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import inspect
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from litellm.types.completion import CompletionRequest
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acompletion_params_odict = inspect.signature(acompletion).parameters
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completion_params_dict = inspect.signature(completion).parameters
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acompletion_params = {
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name: param.annotation for name, param in acompletion_params_odict.items()
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}
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completion_params = {
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name: param.annotation for name, param in completion_params_dict.items()
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}
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keys_acompletion = set(acompletion_params.keys())
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keys_completion = set(completion_params.keys())
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print(keys_acompletion)
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print("\n\n\n")
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print(keys_completion)
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print("diff=", keys_completion - keys_acompletion)
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# Assert that the parameters are the same
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if keys_acompletion != keys_completion:
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pytest.fail(
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"The parameters of the litellm.acompletion function and litellm.completion are not the same. "
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f"Completion has extra keys: {keys_completion - keys_acompletion}"
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)
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# test_acompletion_params()
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@pytest.mark.asyncio
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async def test_langfuse_double_logging():
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import litellm
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litellm.set_verbose = True
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litellm.success_callback = ["langfuse"]
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litellm.failure_callback = ["langfuse"] # logs errors to langfuse
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models = ["gpt-4o-mini", "claude-3-5-haiku-20241022"]
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messages = [
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{"role": "user", "content": "Hello, how are you?"},
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]
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resp = await litellm.acompletion(
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model=models[0],
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messages=messages,
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temperature=0.0,
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fallbacks=models[1:],
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# metadata={"generation_name": "test-gen", "project": "litellm-test"},
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)
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return resp
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