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106 lines
2.8 KiB
Python
106 lines
2.8 KiB
Python
#### What this tests ####
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# This tests if ahealth_check() actually works
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import sys, os
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import traceback
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import pytest
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import litellm, asyncio
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@pytest.mark.asyncio
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async def test_azure_health_check():
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response = await litellm.ahealth_check(
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model_params={
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"model": "azure/chatgpt-v-2",
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"messages": [{"role": "user", "content": "Hey, how's it going?"}],
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"api_key": os.getenv("AZURE_API_KEY"),
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"api_base": os.getenv("AZURE_API_BASE"),
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"api_version": os.getenv("AZURE_API_VERSION"),
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}
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)
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print(f"response: {response}")
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assert "x-ratelimit-remaining-tokens" in response
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return response
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# asyncio.run(test_azure_health_check())
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@pytest.mark.asyncio
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async def test_azure_embedding_health_check():
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response = await litellm.ahealth_check(
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model_params={
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"model": "azure/azure-embedding-model",
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"api_key": os.getenv("AZURE_API_KEY"),
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"api_base": os.getenv("AZURE_API_BASE"),
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"api_version": os.getenv("AZURE_API_VERSION"),
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},
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input=["test for litellm"],
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mode="embedding",
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)
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print(f"response: {response}")
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assert "x-ratelimit-remaining-tokens" in response
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return response
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@pytest.mark.asyncio
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async def test_openai_img_gen_health_check():
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response = await litellm.ahealth_check(
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model_params={
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"model": "dall-e-3",
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"api_key": os.getenv("OPENAI_API_KEY"),
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},
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mode="image_generation",
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prompt="cute baby sea otter",
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)
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print(f"response: {response}")
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assert isinstance(response, dict) and "error" not in response
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return response
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# asyncio.run(test_openai_img_gen_health_check())
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async def test_azure_img_gen_health_check():
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response = await litellm.ahealth_check(
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model_params={
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"model": "azure/",
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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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"api_version": "2023-06-01-preview",
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},
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mode="image_generation",
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prompt="cute baby sea otter",
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)
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assert isinstance(response, dict) and "error" not in response
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return response
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# asyncio.run(test_azure_img_gen_health_check())
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@pytest.mark.asyncio
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async def test_sagemaker_embedding_health_check():
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response = await litellm.ahealth_check(
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model_params={
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"model": "sagemaker/berri-benchmarking-gpt-j-6b-fp16",
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"messages": [{"role": "user", "content": "Hey, how's it going?"}],
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},
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mode="embedding",
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input=["test from litellm"],
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)
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print(f"response: {response}")
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assert isinstance(response, dict)
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return response
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# asyncio.run(test_sagemaker_embedding_health_check())
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