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66 lines
1.8 KiB
Python
66 lines
1.8 KiB
Python
#### What this tests ####
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# This tests error logging (with custom user functions) for the raw `completion` + `embedding` endpoints
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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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) # 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.set_verbose = False
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score = 0
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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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user_message = "Hello, how are you?"
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messages = [{"content": user_message, "role": "user"}]
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# test on openai completion call
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try:
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response = completion(model="gpt-3.5-turbo", messages=messages, logger_fn=logger_fn)
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score += 1
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except:
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print(f"error occurred: {traceback.format_exc()}")
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pass
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# test on non-openai completion call
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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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print(f"claude response: {response}")
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score += 1
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except:
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print(f"error occurred: {traceback.format_exc()}")
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pass
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# # test on openai embedding call
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# try:
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# response = embedding(model='text-embedding-ada-002', input=[user_message], logger_fn=logger_fn)
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# score +=1
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# except:
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# traceback.print_exc()
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# # test on bad azure openai embedding call -> missing azure flag and this isn't an embedding model
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# try:
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# response = embedding(model='chatgpt-test', input=[user_message], logger_fn=logger_fn)
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# except:
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# score +=1 # expect this to fail
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# traceback.print_exc()
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# # test on good azure openai embedding call
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# try:
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# response = embedding(model='azure-embedding-model', input=[user_message], azure=True, logger_fn=logger_fn)
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# score +=1
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# except:
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# traceback.print_exc()
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# print(f"Score: {score}, Overall score: {score/5}")
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