litellm/tests/local_testing/test_router_timeout.py
Krish Dholakia 1e403a8447
Litellm dev 10 29 2024 (#6502)
* fix(core_helpers.py): return None, instead of raising kwargs is None error

Closes https://github.com/BerriAI/litellm/issues/6500

* docs(cost_tracking.md): cleanup doc

* fix(vertex_and_google_ai_studio.py): handle function call with no params passed in

Closes https://github.com/BerriAI/litellm/issues/6495

* test(test_router_timeout.py): add test for router timeout + retry logic

* test: update test to use module level values

* (fix) Prometheus - Log Postgres DB latency, status on prometheus  (#6484)

* fix logging DB fails on prometheus

* unit testing log to otel wrapper

* unit testing for service logger + prometheus

* use LATENCY buckets for service logging

* fix service logging

* docs clarify vertex vs gemini

* (router_strategy/) ensure all async functions use async cache methods (#6489)

* fix router strat

* use async set / get cache in router_strategy

* add coverage for router strategy

* fix imports

* fix batch_get_cache

* use async methods for least busy

* fix least busy use async methods

* fix test_dual_cache_increment

* test async_get_available_deployment when routing_strategy="least-busy"

* (fix) proxy - fix when `STORE_MODEL_IN_DB` should be set (#6492)

* set store_model_in_db at the top

* correctly use store_model_in_db global

* (fix) `PrometheusServicesLogger` `_get_metric` should return metric in Registry  (#6486)

* fix logging DB fails on prometheus

* unit testing log to otel wrapper

* unit testing for service logger + prometheus

* use LATENCY buckets for service logging

* fix service logging

* fix _get_metric in prom services logger

* add clear doc string

* unit testing for prom service logger

* bump: version 1.51.0 → 1.51.1

* Add `azure/gpt-4o-mini-2024-07-18` to model_prices_and_context_window.json (#6477)

* Update utils.py (#6468)

Fixed missing keys

* (perf) Litellm redis router fix - ~100ms improvement (#6483)

* docs(exception_mapping.md): add missing exception types

Fixes https://github.com/Aider-AI/aider/issues/2120#issuecomment-2438971183

* fix(main.py): register custom model pricing with specific key

Ensure custom model pricing is registered to the specific model+provider key combination

* test: make testing more robust for custom pricing

* fix(redis_cache.py): instrument otel logging for sync redis calls

ensures complete coverage for all redis cache calls

* refactor: pass parent_otel_span for redis caching calls in router

allows for more observability into what calls are causing latency issues

* test: update tests with new params

* refactor: ensure e2e otel tracing for router

* refactor(router.py): add more otel tracing acrosss router

catch all latency issues for router requests

* fix: fix linting error

* fix(router.py): fix linting error

* fix: fix test

* test: fix tests

* fix(dual_cache.py): pass ttl to redis cache

* fix: fix param

* perf(cooldown_cache.py): improve cooldown cache, to store cache results in memory for 5s, prevents redis call from being made on each request

reduces 100ms latency per call with caching enabled on router

* fix: fix test

* fix(cooldown_cache.py): handle if a result is None

* fix(cooldown_cache.py): add debug statements

* refactor(dual_cache.py): move to using an in-memory check for batch get cache, to prevent redis from being hit for every call

* fix(cooldown_cache.py): fix linting erropr

* refactor(prometheus.py): move to using standard logging payload for reading the remaining request / tokens

Ensures prometheus token tracking works for anthropic as well

* fix: fix linting error

* fix(redis_cache.py): make sure ttl is always int (handle float values)

Fixes issue where redis_client.ex was not working correctly due to float ttl

* fix: fix linting error

* test: update test

* fix: fix linting error

---------

Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Xingyao Wang <xingyao@all-hands.dev>
Co-authored-by: vibhanshu-ob <115142120+vibhanshu-ob@users.noreply.github.com>
2024-10-29 22:04:16 -07:00

189 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-instant-1.2",
"litellm_params": {
"model": "claude-instant-1.2",
"api_key": "os.environ/ANTHROPIC_API_KEY",
"mock_response": "hello world",
},
"tpm": 20000,
},
]
fallbacks_list = [
{"openai-gpt-4": ["anthropic-claude-instant-1.2"]},
]
# 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.
"""
litellm._turn_on_debug()
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