mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 18:54:30 +00:00
* test: update tests to new deployment model * test: update model name * test: skip cohere rbac issue test * test: update test - replace gpt-4o model
99 lines
3.2 KiB
Python
99 lines
3.2 KiB
Python
import sys
|
|
|
|
import os
|
|
|
|
sys.path.insert(0, os.path.abspath("../.."))
|
|
|
|
import asyncio
|
|
import litellm
|
|
from litellm._logging import verbose_logger
|
|
import logging
|
|
import time
|
|
import pytest
|
|
|
|
|
|
def test_otel_logging_async():
|
|
try:
|
|
os.environ["OTEL_EXPORTER"] = "otlp_http"
|
|
os.environ["OTEL_ENDPOINT"] = (
|
|
"https://exampleopenaiendpoint-production.up.railway.app/traces"
|
|
)
|
|
os.environ["OTEL_HEADERS"] = "Authorization=K0BSwd"
|
|
|
|
def single_run():
|
|
litellm.callbacks = []
|
|
start_time_empty = asyncio.run(make_async_calls())
|
|
print(f"Time with empty callback: {start_time_empty}")
|
|
|
|
litellm.callbacks = ["otel"]
|
|
start_time_otel = asyncio.run(make_async_calls())
|
|
print(f"Time with otel callback: {start_time_otel}")
|
|
|
|
percent_diff = (
|
|
abs(start_time_otel - start_time_empty) / start_time_empty * 100
|
|
)
|
|
print(f"Run performance difference: {percent_diff:.2f}%")
|
|
return percent_diff
|
|
|
|
percent_diffs = [single_run() for _ in range(3)]
|
|
avg_percent_diff = sum(percent_diffs) / len(percent_diffs)
|
|
|
|
print(f"Percentage differences: {percent_diffs}")
|
|
print(f"Average performance difference: {avg_percent_diff:.2f}%")
|
|
|
|
assert (
|
|
avg_percent_diff < 30
|
|
), f"Average performance difference of {avg_percent_diff:.2f}% exceeds 30% threshold"
|
|
|
|
except litellm.Timeout as e:
|
|
pass
|
|
except Exception as e:
|
|
pytest.fail(f"An exception occurred - {e}")
|
|
|
|
|
|
async def make_async_calls(metadata=None, **completion_kwargs):
|
|
total_start_time = asyncio.get_event_loop().time()
|
|
tasks = []
|
|
|
|
async def create_and_run_task():
|
|
task = create_async_task(**completion_kwargs)
|
|
response = await task
|
|
print(f"Response: {response}")
|
|
|
|
for _ in range(3): # Run for 10 seconds
|
|
# Create 100 tasks
|
|
tasks = []
|
|
for _ in range(100):
|
|
tasks.append(asyncio.create_task(create_and_run_task()))
|
|
|
|
# Wait for any remaining tasks to complete
|
|
await asyncio.gather(*tasks)
|
|
|
|
await asyncio.sleep(1)
|
|
|
|
# Calculate the total time taken
|
|
total_time = asyncio.get_event_loop().time() - total_start_time
|
|
|
|
return total_time
|
|
|
|
|
|
def create_async_task(**completion_kwargs):
|
|
"""
|
|
Creates an async task for the litellm.acompletion function.
|
|
This is just the task, but it is not run here.
|
|
To run the task it must be awaited or used in other asyncio coroutine execution functions like asyncio.gather.
|
|
Any kwargs passed to this function will be passed to the litellm.acompletion function.
|
|
By default a standard set of arguments are used for the litellm.acompletion function.
|
|
"""
|
|
completion_args = {
|
|
"model": "openai/chatgpt-v-3",
|
|
"api_version": "2024-02-01",
|
|
"messages": [{"role": "user", "content": "This is a test" * 100}],
|
|
"max_tokens": 5,
|
|
"temperature": 0.7,
|
|
"timeout": 5,
|
|
"user": "langfuse_latency_test_user",
|
|
"mock_response": "Mock response",
|
|
}
|
|
completion_args.update(completion_kwargs)
|
|
return asyncio.create_task(litellm.acompletion(**completion_args))
|