nnnn / litellm /tests /test_llmonitor_integration.py
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# #### What this tests ####
# # This tests if logging to the llmonitor integration actually works
# # Adds the parent directory to the system path
# import sys
# import os
# sys.path.insert(0, os.path.abspath("../.."))
# from litellm import completion, embedding
# import litellm
# litellm.success_callback = ["llmonitor"]
# litellm.failure_callback = ["llmonitor"]
# litellm.set_verbose = True
# def test_chat_openai():
# try:
# response = completion(
# model="gpt-3.5-turbo",
# messages=[{"role": "user", "content": "Hi πŸ‘‹ - i'm openai"}],
# user="ishaan_from_litellm"
# )
# print(response)
# except Exception as e:
# print(e)
# def test_embedding_openai():
# try:
# response = embedding(model="text-embedding-ada-002", input=["test"])
# # Add any assertions here to check the response
# print(f"response: {str(response)[:50]}")
# except Exception as e:
# print(e)
# test_chat_openai()
# # test_embedding_openai()
# def test_llmonitor_logging_function_calling():
# function1 = [
# {
# "name": "get_current_weather",
# "description": "Get the current weather in a given location",
# "parameters": {
# "type": "object",
# "properties": {
# "location": {
# "type": "string",
# "description": "The city and state, e.g. San Francisco, CA",
# },
# "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
# },
# "required": ["location"],
# },
# }
# ]
# try:
# response = completion(model="gpt-3.5-turbo",
# messages=[{
# "role": "user",
# "content": "what's the weather in boston"
# }],
# temperature=0.1,
# functions=function1,
# )
# print(response)
# except Exception as e:
# print(e)
# # test_llmonitor_logging_function_calling()