litellm/tests/local_testing/test_router_debug_logs.py
Yuneng Jiang 6fd988cc63
test(router): ignore deployment-selection logs in the fallback log assertion
simple_shuffle logs the selected deployment at INFO whenever a weight set
applies, so the fallback group's selection line lands between the fallback
notice and the success notice and pushed the notice out of the tail-3 window.
Filter it the same way the neighbouring get_available_deployment noise is
already filtered.
2026-09-15 19:45:33 -07:00

106 lines
3.6 KiB
Python

import asyncio
import os
import time
import traceback
import pytest
import logging
import litellm
from litellm import Router
# this tests debug logs from litellm router and litellm proxy server
from litellm._logging import verbose_logger, verbose_proxy_logger, verbose_router_logger
from litellm.llms.custom_httpx.async_client_cleanup import close_litellm_async_clients
# this tests debug logs from litellm router and litellm proxy server
def test_async_fallbacks(caplog):
# THIS IS A PROD TEST - DO NOT DELETE THIS. Used for testing if litellm proxy verbose logs are human readable
litellm.set_verbose = False
litellm.success_callback = []
litellm.failure_callback = []
verbose_router_logger.setLevel(level=logging.INFO)
verbose_logger.setLevel(logging.CRITICAL + 1)
verbose_proxy_logger.setLevel(logging.CRITICAL + 1)
model_list = [
{
"model_name": "azure/gpt-3.5-turbo",
"litellm_params": {
"model": "azure/gpt-4.1-mini",
"api_key": os.getenv("AZURE_AI_API_KEY"),
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_AI_API_BASE"),
"mock_response": "Hello world",
},
"tpm": 240000,
"rpm": 1800,
},
{
"model_name": "gpt-3.5-turbo",
"litellm_params": {
"model": "gpt-3.5-turbo",
"api_key": "bad-key",
},
"tpm": 1000000,
"rpm": 9000,
},
]
router = Router(
model_list=model_list,
fallbacks=[{"gpt-3.5-turbo": ["azure/gpt-3.5-turbo"]}],
num_retries=1,
)
user_message = "Hello, how are you?"
messages = [{"content": user_message, "role": "user"}]
async def _make_request():
try:
await router.acompletion(
model="gpt-3.5-turbo", messages=messages, max_tokens=1
)
router.reset()
except litellm.Timeout:
pass
except Exception as e:
pytest.fail(f"An exception occurred: {e}")
finally:
router.reset()
# Close cached aiohttp/httpx clients before the event loop ends
# to prevent "Unclosed client session" / "Unclosed connector" warnings.
await close_litellm_async_clients()
asyncio.run(_make_request())
captured_logs = [rec.message for rec in caplog.records]
# on circle ci the captured logs get async cleanup noise from the gc (leaked
# task warnings, plus aiohttp "Unclosed client session"/"Unclosed connector"
# warnings from cached clients other router tests evicted) - filter it out
captured_logs = [
log
for log in captured_logs
if "Task exception was never retrieved" not in log
and "Task was destroyed but it is pending" not in log
and "get_available_deployment" not in log
and "Selected deployment for model" not in log
and "in the Langfuse queue" not in log
and "Unclosed client session" not in log
and "Unclosed connector" not in log
]
print("\n Captured caplog records - ", captured_logs)
# Define the expected log messages
# - error request, falling back notice, success notice
expected_logs = [
"Falling back to model_group = azure/gpt-3.5-turbo",
"litellm.acompletion(model=azure/gpt-4.1-mini)\x1b[32m 200 OK\x1b[0m",
"Successful fallback b/w models.",
]
# Assert that the captured logs match the expected log messages
assert captured_logs[-3:] == expected_logs