litellm-mirror/litellm/tests/test_llmonitor_integration.py
2023-10-20 09:05:14 -07:00

76 lines
2.1 KiB
Python

#### 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 👋 - 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()