litellm/tests/local_testing/test_router_timeout.py
Krish Dholakia 27e18358ab
fix(pattern_match_deployments.py): default to user input if unable to… (#6632)
* fix(pattern_match_deployments.py): default to user input if unable to map based on wildcards

* test: fix test

* test: reset test name

* test: update conftest to reload proxy server module between tests

* ci(config.yml): move langfuse out of local_testing

reduce ci/cd time

* ci(config.yml): cleanup langfuse ci/cd tests

* fix: update test to not use global proxy_server app module

* ci: move caching to a separate test pipeline

speed up ci pipeline

* test: update conftest to check if proxy_server attr exists before reloading

* build(conftest.py): don't block on inability to reload proxy_server

* ci(config.yml): update caching unit test filter to work on 'cache' keyword as well

* fix(encrypt_decrypt_utils.py): use function to get salt key

* test: mark flaky test

* test: handle anthropic overloaded errors

* refactor: create separate ci/cd pipeline for proxy unit tests

make ci/cd faster

* ci(config.yml): add litellm_proxy_unit_testing to build_and_test jobs

* ci(config.yml): generate prisma binaries for proxy unit tests

* test: readd vertex_key.json

* ci(config.yml): remove `-s` from proxy_unit_test cmd

speed up test

* ci: remove any 'debug' logging flag

speed up ci pipeline

* test: fix test

* test(test_braintrust.py): rerun

* test: add delay for braintrust test
2024-11-08 00:55:57 +05:30

188 lines
5.1 KiB
Python

#### What this tests ####
# This tests if the router timeout error handling during fallbacks
import asyncio
import os
import sys
import time
import traceback
import pytest
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
from unittest.mock import patch, MagicMock, AsyncMock
import os
from dotenv import load_dotenv
import litellm
from litellm import Router
load_dotenv()
def test_router_timeouts():
# Model list for OpenAI and Anthropic models
model_list = [
{
"model_name": "openai-gpt-4",
"litellm_params": {
"model": "azure/chatgpt-v-2",
"api_key": "os.environ/AZURE_API_KEY",
"api_base": "os.environ/AZURE_API_BASE",
"api_version": "os.environ/AZURE_API_VERSION",
},
"tpm": 80000,
},
{
"model_name": "anthropic-claude-3-5-haiku-20241022",
"litellm_params": {
"model": "claude-3-5-haiku-20241022",
"api_key": "os.environ/ANTHROPIC_API_KEY",
"mock_response": "hello world",
},
"tpm": 20000,
},
]
fallbacks_list = [
{"openai-gpt-4": ["anthropic-claude-3-5-haiku-20241022"]},
]
# Configure router
router = Router(
model_list=model_list,
fallbacks=fallbacks_list,
routing_strategy="usage-based-routing",
debug_level="INFO",
set_verbose=True,
redis_host=os.getenv("REDIS_HOST"),
redis_password=os.getenv("REDIS_PASSWORD"),
redis_port=int(os.getenv("REDIS_PORT")),
timeout=10,
num_retries=0,
)
print("***** TPM SETTINGS *****")
for model_object in model_list:
print(f"{model_object['model_name']}: {model_object['tpm']} TPM")
# Sample list of questions
questions_list = [
{"content": "Tell me a very long joke.", "modality": "voice"},
]
total_tokens_used = 0
# Process each question
for question in questions_list:
messages = [{"content": question["content"], "role": "user"}]
prompt_tokens = litellm.token_counter(text=question["content"], model="gpt-4")
print("prompt_tokens = ", prompt_tokens)
response = router.completion(
model="openai-gpt-4", messages=messages, timeout=5, num_retries=0
)
total_tokens_used += response.usage.total_tokens
print("Response:", response)
print("********** TOKENS USED SO FAR = ", total_tokens_used)
@pytest.mark.asyncio
async def test_router_timeouts_bedrock():
import uuid
import openai
# Model list for OpenAI and Anthropic models
_model_list = [
{
"model_name": "bedrock",
"litellm_params": {
"model": "bedrock/anthropic.claude-instant-v1",
"timeout": 0.00001,
},
"tpm": 80000,
},
]
# Configure router
router = Router(
model_list=_model_list,
routing_strategy="usage-based-routing",
debug_level="DEBUG",
set_verbose=True,
num_retries=0,
)
litellm.set_verbose = True
try:
response = await router.acompletion(
model="bedrock",
messages=[{"role": "user", "content": f"hello, who are u {uuid.uuid4()}"}],
)
print(response)
pytest.fail("Did not raise error `openai.APITimeoutError`")
except openai.APITimeoutError as e:
print(
"Passed: Raised correct exception. Got openai.APITimeoutError\nGood Job", e
)
print(type(e))
pass
except Exception as e:
pytest.fail(
f"Did not raise error `openai.APITimeoutError`. Instead raised error type: {type(e)}, Error: {e}"
)
@pytest.mark.parametrize(
"num_retries, expected_call_count",
[(0, 1), (1, 2), (2, 3), (3, 4)],
)
def test_router_timeout_with_retries_anthropic_model(num_retries, expected_call_count):
"""
If request hits custom timeout, ensure it's retried.
"""
from litellm.llms.custom_httpx.http_handler import HTTPHandler
import time
litellm.num_retries = num_retries
litellm.request_timeout = 0.000001
router = Router(
model_list=[
{
"model_name": "claude-3-haiku",
"litellm_params": {
"model": "anthropic/claude-3-haiku-20240307",
},
}
],
)
custom_client = HTTPHandler()
with patch.object(custom_client, "post", new=MagicMock()) as mock_client:
try:
def delayed_response(*args, **kwargs):
time.sleep(0.01) # Exceeds the 0.000001 timeout
raise TimeoutError("Request timed out.")
mock_client.side_effect = delayed_response
router.completion(
model="claude-3-haiku",
messages=[{"role": "user", "content": "hello, who are u"}],
client=custom_client,
)
except litellm.Timeout:
pass
assert mock_client.call_count == expected_call_count