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https://github.com/BerriAI/litellm.git
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e9d40a8f73
A name bound twice keeps only the second binding. In `tests/` that is nearly always a repeated import, harmless but misleading, and the same rule is what catches the cases that are not harmless: a local that shadows an import the module still calls, and a second `def test_x` that quietly replaces the first. 311 of the 344 sites were repeated imports and came out with ruff's own fix. The remaining 33 needed a decision. Four modules imported a name they never used because a local definition below already shadowed it. Two comprehensions bound `call` over `unittest.mock.call`, which those modules import and use. One test rebound the two module handles its nested reload closure had captured. One class attribute shadowed an unused `status` import. The load-test fixtures move to a conftest, which is how pytest is meant to share them, so the test module no longer imports three fixture names it never calls. The nine `prisma_client` parameters keep a narrow `noqa`: pytest resolves that fixture by name before the body runs, so the parameter never shadows anything.
109 lines
3.6 KiB
Python
109 lines
3.6 KiB
Python
import asyncio
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import os
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import sys
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import time
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import traceback
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import pytest
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import logging
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import litellm
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from litellm import Router
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# this tests debug logs from litellm router and litellm proxy server
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from litellm._logging import verbose_logger, verbose_proxy_logger, verbose_router_logger
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from litellm.llms.custom_httpx.async_client_cleanup import close_litellm_async_clients
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# this tests debug logs from litellm router and litellm proxy server
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def test_async_fallbacks(caplog):
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# THIS IS A PROD TEST - DO NOT DELETE THIS. Used for testing if litellm proxy verbose logs are human readable
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litellm.set_verbose = False
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litellm.success_callback = []
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litellm.failure_callback = []
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verbose_router_logger.setLevel(level=logging.INFO)
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verbose_logger.setLevel(logging.CRITICAL + 1)
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verbose_proxy_logger.setLevel(logging.CRITICAL + 1)
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model_list = [
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{
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"model_name": "azure/gpt-3.5-turbo",
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"litellm_params": {
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"model": "azure/gpt-4.1-mini",
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"api_key": os.getenv("AZURE_AI_API_KEY"),
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"api_version": os.getenv("AZURE_API_VERSION"),
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"api_base": os.getenv("AZURE_AI_API_BASE"),
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"mock_response": "Hello world",
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},
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"tpm": 240000,
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"rpm": 1800,
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},
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{
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"model_name": "gpt-3.5-turbo",
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"litellm_params": {
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"model": "gpt-3.5-turbo",
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"api_key": "bad-key",
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},
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"tpm": 1000000,
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"rpm": 9000,
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},
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]
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router = Router(
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model_list=model_list,
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fallbacks=[{"gpt-3.5-turbo": ["azure/gpt-3.5-turbo"]}],
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num_retries=1,
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)
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user_message = "Hello, how are you?"
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messages = [{"content": user_message, "role": "user"}]
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async def _make_request():
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try:
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await router.acompletion(
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model="gpt-3.5-turbo", messages=messages, max_tokens=1
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)
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router.reset()
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except litellm.Timeout:
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pass
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except Exception as e:
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pytest.fail(f"An exception occurred: {e}")
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finally:
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router.reset()
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# Close cached aiohttp/httpx clients before the event loop ends
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# to prevent "Unclosed client session" / "Unclosed connector" warnings.
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await close_litellm_async_clients()
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asyncio.run(_make_request())
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captured_logs = [rec.message for rec in caplog.records]
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# on circle ci the captured logs get async cleanup noise from the gc (leaked
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# task warnings, plus aiohttp "Unclosed client session"/"Unclosed connector"
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# warnings from cached clients other router tests evicted) - filter it out
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captured_logs = [
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log
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for log in captured_logs
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if "Task exception was never retrieved" not in log
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and "Task was destroyed but it is pending" not in log
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and "get_available_deployment" not in log
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and "in the Langfuse queue" not in log
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and "Unclosed client session" not in log
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and "Unclosed connector" not in log
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]
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print("\n Captured caplog records - ", captured_logs)
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# Define the expected log messages
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# - error request, falling back notice, success notice
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expected_logs = [
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"Falling back to model_group = azure/gpt-3.5-turbo",
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"litellm.acompletion(model=azure/gpt-4.1-mini)\x1b[32m 200 OK\x1b[0m",
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"Successful fallback b/w models.",
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]
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# Assert that the captured logs match the expected log messages
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assert captured_logs[-3:] == expected_logs
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