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90 lines
2.6 KiB
Python
90 lines
2.6 KiB
Python
#### What this tests ####
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# This tests error logging (with custom user functions) for the `completion` + `embedding` endpoints w/ callbacks
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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
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from litellm import embedding, completion
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litellm.success_callback = ["posthog", "helicone"]
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litellm.failure_callback = ["sentry", "posthog"]
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litellm.set_verbose = True
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def logger_fn(model_call_object: dict):
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# print(f"model call details: {model_call_object}")
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pass
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user_message = "Hello, how are you?"
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messages = [{"content": user_message, "role": "user"}]
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def test_completion_openai():
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try:
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print("running query")
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response = completion(
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model="gpt-3.5-turbo", messages=messages, logger_fn=logger_fn
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)
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print(f"response: {response}")
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# Add any assertions here to check the response
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except Exception as e:
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traceback.print_exc()
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pytest.fail(f"Error occurred: {e}")
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def test_completion_claude():
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try:
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response = completion(
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model="claude-instant-1", messages=messages, logger_fn=logger_fn
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)
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# Add any assertions here to check the response
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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def test_completion_non_openai():
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try:
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response = completion(
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model="command-nightly", messages=messages, logger_fn=logger_fn
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)
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# Add any assertions here to check the response
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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def test_embedding_openai():
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try:
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response = embedding(
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model="text-embedding-ada-002", input=[user_message], logger_fn=logger_fn
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)
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# Add any assertions here to check the response
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print(f"response: {str(response)[:50]}")
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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def test_bad_azure_embedding():
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try:
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response = embedding(
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model="chatgpt-test", input=[user_message], logger_fn=logger_fn
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)
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# Add any assertions here to check the response
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print(f"response: {str(response)[:50]}")
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except Exception as e:
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pass
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# def test_good_azure_embedding():
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# try:
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# response = embedding(model='azure/azure-embedding-model', input=[user_message], logger_fn=logger_fn)
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# # Add any assertions here to check the response
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# print(f"response: {str(response)[:50]}")
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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