litellm-mirror/litellm/tests/test_logging.py
2023-07-31 18:26:16 -07:00

51 lines
1.6 KiB
Python

#### What this tests ####
# This tests error logging (with custom user functions) for the raw `completion` + `embedding` endpoints
import sys, os
import traceback
sys.path.insert(0, os.path.abspath('../..')) # Adds the parent directory to the system path
import litellm
from litellm import embedding, completion
litellm.set_verbose = True
def logger_fn(model_call_object: dict):
print(f"model call details: {model_call_object}")
user_message = "Hello, how are you?"
messages = [{ "content": user_message,"role": "user"}]
# test on openai completion call
try:
response = completion(model="gpt-3.5-turbo", messages=messages)
except:
print(f"error occurred: {traceback.format_exc()}")
pass
# test on non-openai completion call
try:
response = completion(model="claude-instant-1", messages=messages, logger_fn=logger_fn)
except:
print(f"error occurred: {traceback.format_exc()}")
pass
# test on openai embedding call
try:
response = embedding(model='text-embedding-ada-002', input=[user_message], logger_fn=logger_fn)
print(f"response: {str(response)[:50]}")
except:
traceback.print_exc()
# test on bad azure openai embedding call -> missing azure flag and this isn't an embedding model
try:
response = embedding(model='chatgpt-test', input=[user_message], logger_fn=logger_fn)
print(f"response: {str(response)[:50]}")
except:
traceback.print_exc()
# test on good azure openai embedding call
try:
response = embedding(model='azure-embedding-model', input=[user_message], azure=True, logger_fn=logger_fn)
print(f"response: {str(response)[:50]}")
except:
traceback.print_exc()