litellm/tests/unit/proxy/hooks/test_dynamic_rate_limiter.py
Mateo Wang 58258409c9
refactor(proxy): expose public names for private proxy helpers (#45170)
* refactor(proxy): expose public names for private proxy helpers

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): keep original class names behind public aliases

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): preserve internal callback filtering

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): keep _PROXY_ class names for managed files hooks

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): keep old private names in package exports

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): preserve recursive auth helper name

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(proxy): align MCP limiter tests with server enforcement

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(proxy): match main's MCP limiter tests

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): keep old private names bound in importing modules

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): preserve compatibility imports through strict lint

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(proxy): use exact pyright suppression in password helper test

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* style(proxy): add reasons to compatibility import noqa comments

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(proxy): update IN-list baseline for renamed helpers

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-07 18:59:27 -07:00

557 lines
18 KiB
Python

from datetime import datetime, timezone
from typing import Final
import asyncio, importlib, litellm, os, pytest
from litellm.caching.caching import DualCache
from litellm.proxy.hooks.dynamic_rate_limiter import(
PROXY_DynamicRateLimitHandler as DynamicRateLimitHandler,
DynamicRateLimiterCache,
PROXY_DynamicRateLimitHandler,
)
from litellm.types.utils import HiddenParams, ModelResponse
from litellm import DualCache as DualCache_dynamic_rate, Router
from litellm._uuid import uuid
from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER
from litellm.proxy._types import UserAPIKeyAuth
from litellm.utils import _invalidate_model_cost_lowercase_map
from tests._vcr_conftest_common import install_live_call_probe, record_vcr_outcome
from typing import Optional
@pytest.mark.asyncio
async def test_sadd_and_get_share_injected_clock_window():
dual_cache = DualCache()
cache = DynamicRateLimiterCache(
cache=dual_cache,
time_fn=lambda: datetime(2024, 1, 1, 10, 30, 0, tzinfo=timezone.utc),
)
await cache.async_set_cache_sadd(model="my-fake-model", value=["p1", "p2", "p3"])
assert await cache.async_get_cache(model="my-fake-model") == 3
assert await dual_cache.async_get_cache(key="10-30:my-fake-model") is not None
@pytest.mark.asyncio
async def test_minute_rollover_between_sadd_and_get_reads_empty_window():
ticks = iter(
(
datetime(2024, 1, 1, 10, 30, 59, 999999, tzinfo=timezone.utc),
datetime(2024, 1, 1, 10, 31, 0, 0, tzinfo=timezone.utc),
)
)
cache = DynamicRateLimiterCache(cache=DualCache(), time_fn=lambda: next(ticks))
await cache.async_set_cache_sadd(model="my-fake-model", value=["p1"])
assert await cache.async_get_cache(model="my-fake-model") is None
@pytest.mark.asyncio
async def test_handler_threads_time_fn_to_internal_cache():
handler = PROXY_DynamicRateLimitHandler(
internal_usage_cache=DualCache(),
time_fn=lambda: datetime(2024, 1, 1, 10, 30, 0, tzinfo=timezone.utc),
)
await handler.internal_usage_cache.async_set_cache_sadd(model="my-fake-model", value=["p1", "p2"])
assert await handler.internal_usage_cache.async_get_cache(model="my-fake-model") == 2
@pytest.mark.asyncio
async def test_success_hook_updates_existing_hidden_params_storage() -> None:
model_id: Final = "rate-limit-deployment"
router: Final = Router(
model_list=[
{
"model_name": "my-fake-model",
"litellm_params": {"model": "gpt-3.5-turbo", "api_key": "test-key", "tpm": 100, "rpm": 10},
"model_info": {"id": model_id},
}
]
)
handler: Final = PROXY_DynamicRateLimitHandler(internal_usage_cache=DualCache())
handler.update_variables(llm_router=router)
response: Final = ModelResponse()
hidden_params: Final = HiddenParams(model_id=model_id)
response._hidden_params = hidden_params
result: Final = await handler.async_post_call_success_hook(
data={},
user_api_key_dict=UserAPIKeyAuth(metadata={}),
response=response,
)
assert result is response
assert response._hidden_params is hidden_params
assert response.hidden_params["additional_headers"]["x-litellm-model_group"] == "my-fake-model"
@pytest.fixture()
def _vcr_outcome_gate(request, vcr):
install_live_call_probe(request, vcr)
yield
record_vcr_outcome(request, vcr)
@pytest.fixture(scope="function")
def isolate_litellm_state():
"""
Per-function isolation fixture.
Resets litellm globals to their true defaults before each test and
restores them afterward, so tests don't leak side effects.
Works safely under pytest-xdist parallel execution.
"""
original_state = {}
for attr in (
"callbacks",
"success_callback",
"failure_callback",
"_async_success_callback",
"_async_failure_callback",
):
if hasattr(litellm, attr):
val = getattr(litellm, attr)
original_state[attr] = val.copy() if val else []
for attr in ("pre_call_rules", "post_call_rules"):
if hasattr(litellm, attr):
val = getattr(litellm, attr)
original_state[attr] = val.copy() if val else []
for attr in _SCALAR_DEFAULTS:
if hasattr(litellm, attr):
original_state[attr] = getattr(litellm, attr)
if hasattr(litellm, "in_memory_llm_clients_cache"):
litellm.in_memory_llm_clients_cache.flush_cache()
for attr in (
"callbacks",
"success_callback",
"failure_callback",
"_async_success_callback",
"_async_failure_callback",
"pre_call_rules",
"post_call_rules",
):
if hasattr(litellm, attr):
setattr(litellm, attr, [])
for attr, default_val in _SCALAR_DEFAULTS.items():
if hasattr(litellm, attr):
setattr(litellm, attr, default_val)
yield
asyncio.run(GLOBAL_LOGGING_WORKER.clear_queue())
if hasattr(litellm, "in_memory_llm_clients_cache"):
litellm.in_memory_llm_clients_cache.flush_cache()
for attr, original_value in original_state.items():
if hasattr(litellm, attr):
setattr(litellm, attr, original_value)
_invalidate_model_cost_lowercase_map()
_SCALAR_DEFAULTS = {
"num_retries": getattr(litellm, "num_retries", None),
"num_retries_per_request": getattr(litellm, "num_retries_per_request", None),
"request_timeout": getattr(litellm, "request_timeout", None),
"set_verbose": getattr(litellm, "set_verbose", False),
"cache": getattr(litellm, "cache", None),
"allowed_fails": getattr(litellm, "allowed_fails", 3),
"default_fallbacks": getattr(litellm, "default_fallbacks", None),
"enable_azure_ad_token_refresh": getattr(litellm, "enable_azure_ad_token_refresh", None),
"tag_budget_config": getattr(litellm, "tag_budget_config", None),
"model_cost": getattr(litellm, "model_cost", None),
"token_counter": getattr(litellm, "token_counter", None),
"disable_aiohttp_transport": getattr(litellm, "disable_aiohttp_transport", False),
"force_ipv4": getattr(litellm, "force_ipv4", False),
"drop_params": getattr(litellm, "drop_params", None),
"modify_params": getattr(litellm, "modify_params", False),
"api_base": getattr(litellm, "api_base", None),
"api_key": getattr(litellm, "api_key", None),
}
@pytest.fixture(scope="module")
def setup_and_teardown():
"""
Module-scoped setup. Reloads litellm only in single-process mode
(skipped under xdist to avoid cross-worker interference).
"""
import litellm
worker_id = os.environ.get("PYTEST_XDIST_WORKER", None)
if worker_id is None:
importlib.reload(litellm)
try:
if hasattr(litellm, "proxy") and hasattr(litellm.proxy, "proxy_server"):
import litellm.proxy.proxy_server
importlib.reload(litellm.proxy.proxy_server)
except Exception as e:
print(f"Error reloading litellm.proxy.proxy_server: {e}")
if hasattr(litellm, "in_memory_llm_clients_cache"):
litellm.in_memory_llm_clients_cache.flush_cache()
yield
@pytest.fixture
def _pr4_dynamic_rate_limit_env(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setenv("LITELLM_LICENSE", "pr4-test-license")
"""
Basic test cases:
- If 1 'active' project => give all tpm
- If 2 'active' projects => divide tpm in 2
"""
@pytest.fixture
def dynamic_rate_limit_handler() -> DynamicRateLimitHandler:
internal_cache = DualCache_dynamic_rate()
frozen_now = datetime(2024, 1, 1, 10, 30, 0, tzinfo=timezone.utc)
return DynamicRateLimitHandler(internal_usage_cache=internal_cache, time_fn=lambda: frozen_now)
@pytest.fixture
def mock_response() -> litellm.ModelResponse:
return litellm.ModelResponse(
**{
"id": "chatcmpl-abc123",
"object": "chat.completion",
"created": 1699896916,
"model": "gpt-3.5-turbo-0125",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": None,
"tool_calls": [
{
"id": "call_abc123",
"type": "function",
"function": {
"name": "get_current_weather",
"arguments": '{\n"location": "Boston, MA"\n}',
},
}
],
},
"logprobs": None,
"finish_reason": "tool_calls",
}
],
"usage": {"prompt_tokens": 5, "completion_tokens": 5, "total_tokens": 10},
}
)
@pytest.fixture
def user_api_key_auth() -> UserAPIKeyAuth:
return UserAPIKeyAuth()
@pytest.mark.usefixtures(
"_pr4_dynamic_rate_limit_env",
"_vcr_outcome_gate",
"isolate_litellm_state",
"setup_and_teardown",
)
@pytest.mark.parametrize("num_projects", [1, 2, 100])
@pytest.mark.asyncio
@pytest.mark.flaky(retries=3, delay=1)
async def test_available_tpm(num_projects, dynamic_rate_limit_handler):
model = "my-fake-model"
## SET CACHE W/ ACTIVE PROJECTS
projects = [str(uuid.uuid4()) for _ in range(num_projects)]
await dynamic_rate_limit_handler.internal_usage_cache.async_set_cache_sadd(model=model, value=projects)
model_tpm = 100
llm_router = Router(
model_list=[
{
"model_name": model,
"litellm_params": {
"model": "gpt-3.5-turbo",
"api_key": "my-key",
"api_base": "my-base",
"tpm": model_tpm,
},
}
]
)
dynamic_rate_limit_handler.update_variables(llm_router=llm_router)
## CHECK AVAILABLE TPM PER PROJECT
resp = await dynamic_rate_limit_handler.check_available_usage(model=model)
availability = resp[0]
expected_availability = int(model_tpm / num_projects)
assert availability == expected_availability
@pytest.mark.usefixtures(
"_pr4_dynamic_rate_limit_env",
"_vcr_outcome_gate",
"isolate_litellm_state",
"setup_and_teardown",
)
@pytest.mark.parametrize("num_projects", [1, 2, 100])
@pytest.mark.asyncio
@pytest.mark.flaky(retries=3, delay=1)
async def test_available_rpm(num_projects, dynamic_rate_limit_handler):
model = "my-fake-model"
## SET CACHE W/ ACTIVE PROJECTS
projects = [str(uuid.uuid4()) for _ in range(num_projects)]
await dynamic_rate_limit_handler.internal_usage_cache.async_set_cache_sadd(model=model, value=projects)
model_rpm = 100
llm_router = Router(
model_list=[
{
"model_name": model,
"litellm_params": {
"model": "gpt-3.5-turbo",
"api_key": "my-key",
"api_base": "my-base",
"rpm": model_rpm,
},
}
]
)
dynamic_rate_limit_handler.update_variables(llm_router=llm_router)
## CHECK AVAILABLE rpm PER PROJECT
resp = await dynamic_rate_limit_handler.check_available_usage(model=model)
availability = resp[1]
expected_availability = int(model_rpm / num_projects)
assert availability == expected_availability
@pytest.mark.usefixtures(
"_pr4_dynamic_rate_limit_env",
"_vcr_outcome_gate",
"isolate_litellm_state",
"setup_and_teardown",
)
@pytest.mark.parametrize("usage", ["rpm", "tpm"])
@pytest.mark.asyncio
async def test_rate_limit_raised(dynamic_rate_limit_handler, user_api_key_auth, usage):
"""
Unit test. Tests if rate limit error raised when quota exhausted.
"""
from fastapi import HTTPException
model = "my-fake-model"
## SET CACHE W/ ACTIVE PROJECTS
projects = [str(uuid.uuid4())]
await dynamic_rate_limit_handler.internal_usage_cache.async_set_cache_sadd(model=model, value=projects)
model_usage = 0
llm_router = Router(
model_list=[
{
"model_name": model,
"litellm_params": {
"model": "gpt-3.5-turbo",
"api_key": "my-key",
"api_base": "my-base",
usage: model_usage,
},
}
]
)
dynamic_rate_limit_handler.update_variables(llm_router=llm_router)
## CHECK AVAILABLE TPM PER PROJECT
resp = await dynamic_rate_limit_handler.check_available_usage(model=model)
if usage == "tpm":
availability = resp[0]
else:
availability = resp[1]
expected_availability = 0
assert availability == expected_availability
## CHECK if exception raised
with pytest.raises(HTTPException) as exc_info:
await dynamic_rate_limit_handler.async_pre_call_hook(
user_api_key_dict=user_api_key_auth,
cache=DualCache_dynamic_rate(),
data={"model": model},
call_type="completion",
)
e = exc_info.value
assert e.status_code == 429 # check if rate limit error raised
@pytest.mark.usefixtures(
"_pr4_dynamic_rate_limit_env",
"_vcr_outcome_gate",
"isolate_litellm_state",
"setup_and_teardown",
)
@pytest.mark.asyncio
async def test_base_case(dynamic_rate_limit_handler, mock_response):
"""
If just 1 active project
it should get all the quota
= allow request to go through
- update token usage
- exhaust all tpm with just 1 project
- assert ratelimiterror raised at 100%+1 tpm
"""
model = "my-fake-model"
## model tpm - 50
model_tpm = 50
## tpm per request - 10
setattr(
mock_response,
"usage",
litellm.Usage(prompt_tokens=5, completion_tokens=5, total_tokens=10),
)
llm_router = Router(
model_list=[
{
"model_name": model,
"litellm_params": {
"model": "gpt-3.5-turbo",
"api_key": "my-key",
"api_base": "my-base",
"tpm": model_tpm,
"mock_response": mock_response,
},
}
]
)
dynamic_rate_limit_handler.update_variables(llm_router=llm_router)
prev_availability: Optional[int] = None
allowed_fails = 1
for _ in range(2):
try:
# check availability
resp = await dynamic_rate_limit_handler.check_available_usage(model=model)
availability = resp[0]
print("prev_availability={}, availability={}".format(prev_availability, availability))
## assert availability updated
if prev_availability is not None and availability is not None:
assert availability == prev_availability - 10
prev_availability = availability
# make call
await llm_router.acompletion(model=model, messages=[{"role": "user", "content": "hey!"}])
await asyncio.sleep(3)
except Exception:
if allowed_fails > 0:
allowed_fails -= 1
else:
raise
@pytest.mark.usefixtures(
"_pr4_dynamic_rate_limit_env",
"_vcr_outcome_gate",
"isolate_litellm_state",
"setup_and_teardown",
)
@pytest.mark.asyncio
@pytest.mark.flaky(retries=3, delay=1)
async def test_update_cache(dynamic_rate_limit_handler, mock_response, user_api_key_auth):
"""
Check if active project correctly updated
"""
model = "my-fake-model"
model_tpm = 50
llm_router = Router(
model_list=[
{
"model_name": model,
"litellm_params": {
"model": "gpt-3.5-turbo",
"api_key": "my-key",
"api_base": "my-base",
"tpm": model_tpm,
"mock_response": mock_response,
},
}
]
)
dynamic_rate_limit_handler.update_variables(llm_router=llm_router)
## INITIAL ACTIVE PROJECTS - ASSERT NONE
resp = await dynamic_rate_limit_handler.check_available_usage(model=model)
active_projects = resp[-1]
assert active_projects is None
## MAKE CALL
await dynamic_rate_limit_handler.async_pre_call_hook(
user_api_key_dict=user_api_key_auth,
cache=DualCache_dynamic_rate(),
data={"model": model},
call_type="completion",
)
await asyncio.sleep(2)
## INITIAL ACTIVE PROJECTS - ASSERT 1
resp = await dynamic_rate_limit_handler.check_available_usage(model=model)
active_projects = resp[-1]
assert active_projects == 1
@pytest.mark.usefixtures(
"_pr4_dynamic_rate_limit_env",
"_vcr_outcome_gate",
"isolate_litellm_state",
"setup_and_teardown",
)
@pytest.mark.parametrize("num_projects", [1, 2, 100])
@pytest.mark.asyncio
async def test_priority_reservation(num_projects, dynamic_rate_limit_handler):
"""
If reservation is set + `mock_testing_reservation` passed in
assert correct rpm is reserved
"""
model = "my-fake-model"
## SET CACHE W/ ACTIVE PROJECTS
projects = [str(uuid.uuid4()) for _ in range(num_projects)]
await dynamic_rate_limit_handler.internal_usage_cache.async_set_cache_sadd(model=model, value=projects)
litellm.priority_reservation = {"dev": 0.1, "prod": 0.9}
model_usage = 100
llm_router = Router(
model_list=[
{
"model_name": model,
"litellm_params": {
"model": "gpt-3.5-turbo",
"api_key": "my-key",
"api_base": "my-base",
"rpm": model_usage,
},
}
]
)
dynamic_rate_limit_handler.update_variables(llm_router=llm_router)
## CHECK AVAILABLE TPM PER PROJECT
resp = await dynamic_rate_limit_handler.check_available_usage(model=model, priority="prod")
availability = resp[1]
expected_availability = int(model_usage * litellm.priority_reservation["prod"] / num_projects)
assert availability == expected_availability