test fixes
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@ -300,16 +300,16 @@ async def test_azure_ai_request_format():
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@pytest.mark.asyncio
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@pytest.mark.parametrize("model", ["azure/gpt5_series/gpt-5", "azure/gpt-5"])
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@pytest.mark.parametrize("model", ["azure/gpt5_series/gpt-5-mini", "azure/gpt-5-mini"])
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async def test_azure_gpt5_reasoning(model):
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litellm._turn_on_debug()
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response = await litellm.acompletion(
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model="azure/gpt5_series/gpt-5",
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model=model,
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messages=[{"role": "user", "content": "What is the capital of France?"}],
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reasoning_effort="minimal",
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max_tokens=10,
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api_base=os.getenv("AZURE_GPT5_API_BASE"),
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api_key=os.getenv("AZURE_GPT5_API_KEY"),
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api_base=os.getenv("AZURE_API_BASE"),
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api_key=os.getenv("AZURE_API_KEY"),
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)
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print("response: ", response)
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assert response.choices[0].message.content is not None
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@ -630,20 +630,3 @@ def test_azure_openai_responses_bridge():
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== "test-azure-computer-use-preview"
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)
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assert mock_responses.call_args.kwargs["custom_llm_provider"] == "azure"
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def test_azure_openai_gpt_5_responses_api():
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try:
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from litellm import responses
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litellm._turn_on_debug()
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response = responses(
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model="azure/gpt-5",
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input="Hi good morning",
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api_key=os.getenv("AZURE_GPT5_API_KEY"),
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api_base=os.getenv("AZURE_GPT5_API_BASE"),
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)
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print(f"response: {response}")
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except litellm.RateLimitError:
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pytest.skip("Skipping test due to RateLimitError")
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