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Add key-level multi-instance tpm/rpm/max parallel request limiting (#10458)

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* fix: initial commit of v2 parallel request limiter hook

enables multi-instance rate limiting to work

* fix: subsequent commit with additional refactors

* fix(parallel_request_limiter_v2.py): cleanup initial call hook

simplify it

* fix(parallel_request_limiter_v2.py): working v2 parallel request limiter

* fix: more updates - still not passing testing

* fix(test_parallel_request_limiter_v2.py): update test + add conftest

* fix: fix ruff checks

* fix(parallel_request_limiter_v2.py): use pull via pattern method to load in keys instance wouldn't have seen yet

Fixes issue where redis syncing was not pulling key until instance had seen it

* test: update testing to cover tpm and rpm

* fix(parallel_request_limiter_v2.py): fix ruff errors

* fix(proxy/hooks/__init__.py): feature flag export

* fix(proxy/hooks/__init_.py): fix linting error

* ci(config.yml): add tests/enterprise to ci/cd

* fix: fix ruff check

* test: update testing
This commit is contained in:
Krish Dholakia 2025-04-30 21:32:31 -07:00 committed by GitHub
parent 616c1ad666
commit 711601e22a
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
15 changed files with 987 additions and 58 deletions
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2
.circleci/config.yml
View File

@ -839,7 +839,7 @@ jobs:
command: |
pwd
ls
python -m pytest -vv tests/litellm --cov=litellm --cov-report=xml -x -s -v --junitxml=test-results/junit.xml --durations=5
python -m pytest -vv tests/litellm tests/enterprise --cov=litellm --cov-report=xml -x -s -v --junitxml=test-results/junit.xml --durations=5
no_output_timeout: 120m
- run:
name: Rename the coverage files

6
.pre-commit-config.yaml
View File

@ -6,20 +6,20 @@ repos:
entry: pyright
language: system
types: [python]
files: ^(litellm/|litellm_proxy_extras/)
files: ^(litellm/|litellm_proxy_extras/|enterprise/)
- id: isort
name: isort
entry: isort
language: system
types: [python]
files: (litellm/|litellm_proxy_extras/).*\.py
files: (litellm/|litellm_proxy_extras/|enterprise/).*\.py
exclude: ^litellm/__init__.py$
- id: black
name: black
entry: poetry run black
language: system
types: [python]
files: (litellm/|litellm_proxy_extras/).*\.py
files: (litellm/|litellm_proxy_extras/|enterprise/).*\.py
- repo: https://github.com/pycqa/flake8
rev: 7.0.0 # The version of flake8 to use
hooks:

6
enterprise/enterprise_callbacks/example_logging_api.py
View File

@ -7,11 +7,11 @@ app = FastAPI()
@app.post("/log-event")
async def log_event(request: Request):
try:
print("Received /log-event request")
print("Received /log-event request") # noqa
# Assuming the incoming request has JSON data
data = await request.json()
print("Received request data:")
print(data)
print("Received request data:") # noqa
print(data) # noqa
# Your additional logic can go here
# For now, just printing the received data

4
enterprise/enterprise_hooks/blocked_user_list.py
View File

@ -96,7 +96,7 @@ class _ENTERPRISE_BlockedUserList(CustomLogger):
if end_user_obj is None: # user not in db - assume not blocked
end_user_obj = LiteLLM_EndUserTable(user_id=user, blocked=False)
cache.set_cache(key=cache_key, value=end_user_obj, ttl=60)
if end_user_obj is not None and end_user_obj.blocked == True:
if end_user_obj is not None and end_user_obj.blocked is True:
raise HTTPException(
status_code=400,
detail={
@ -105,7 +105,7 @@ class _ENTERPRISE_BlockedUserList(CustomLogger):
)
elif (
end_user_cache_obj is not None
and end_user_cache_obj.blocked == True
and end_user_cache_obj.blocked is True
):
raise HTTPException(
status_code=400,

10
enterprise/enterprise_hooks/llm_guard.py
View File

@ -29,7 +29,7 @@ class _ENTERPRISE_LLMGuard(CustomLogger):
):
self.mock_redacted_text = mock_redacted_text
self.llm_guard_mode = litellm.llm_guard_mode
if mock_testing == True: # for testing purposes only
if mock_testing is True: # for testing purposes only
return
self.llm_guard_api_base = get_secret_str("LLM_GUARD_API_BASE", None)
if self.llm_guard_api_base is None:
@ -69,7 +69,7 @@ class _ENTERPRISE_LLMGuard(CustomLogger):
if redacted_text is not None:
if (
redacted_text.get("is_valid", None) is not None
and redacted_text["is_valid"] != True
and redacted_text["is_valid"] is False
):
raise HTTPException(
status_code=400,
@ -100,7 +100,7 @@ class _ENTERPRISE_LLMGuard(CustomLogger):
)
if (
user_api_key_dict.permissions.get("enable_llm_guard_check", False)
== True
is True
):
return True
elif self.llm_guard_mode == "all":
@ -111,7 +111,7 @@ class _ENTERPRISE_LLMGuard(CustomLogger):
permissions = metadata.get("permissions", {})
if (
"enable_llm_guard_check" in permissions
and permissions["enable_llm_guard_check"] == True
and permissions["enable_llm_guard_check"] is True
):
return True
return False
@ -140,7 +140,7 @@ class _ENTERPRISE_LLMGuard(CustomLogger):
)
_proceed = self.should_proceed(user_api_key_dict=user_api_key_dict, data=data)
if _proceed == False:
if _proceed is False:
return
self.print_verbose("Makes LLM Guard Check")

384
enterprise/enterprise_hooks/parallel_request_limiter_v2.py Normal file
View File

@ -0,0 +1,384 @@
"""
V2 Implementation of Parallel Requests, TPM, RPM Limiting on the proxy
Designed to work on a multi-instance setup, where multiple instances are writing to redis simultaneously
"""
import sys
from datetime import datetime, timedelta
from typing import (
TYPE_CHECKING,
Any,
List,
Literal,
Optional,
Tuple,
TypedDict,
Union,
cast,
)
from fastapi import HTTPException
import litellm
from litellm import DualCache, ModelResponse
from litellm._logging import verbose_proxy_logger
from litellm.integrations.custom_logger import CustomLogger
from litellm.litellm_core_utils.core_helpers import _get_parent_otel_span_from_kwargs
from litellm.proxy._types import CommonProxyErrors, UserAPIKeyAuth
from litellm.router_strategy.base_routing_strategy import BaseRoutingStrategy
if TYPE_CHECKING:
from opentelemetry.trace import Span as _Span
from litellm.proxy.utils import InternalUsageCache as _InternalUsageCache
Span = Union[_Span, Any]
InternalUsageCache = _InternalUsageCache
else:
Span = Any
InternalUsageCache = Any
class CacheObject(TypedDict):
current_global_requests: Optional[dict]
request_count_api_key: Optional[int]
request_count_api_key_model: Optional[dict]
request_count_user_id: Optional[dict]
request_count_team_id: Optional[dict]
request_count_end_user_id: Optional[dict]
rpm_api_key: Optional[int]
tpm_api_key: Optional[int]
RateLimitGroups = Literal["request_count", "tpm", "rpm"]
class _PROXY_MaxParallelRequestsHandler(BaseRoutingStrategy, CustomLogger):
# Class variables or attributes
def __init__(self, internal_usage_cache: InternalUsageCache):
self.internal_usage_cache = internal_usage_cache
BaseRoutingStrategy.__init__(
self,
dual_cache=internal_usage_cache.dual_cache,
should_batch_redis_writes=True,
default_sync_interval=0.01,
)
def print_verbose(self, print_statement):
try:
verbose_proxy_logger.debug(print_statement)
if litellm.set_verbose:
print(print_statement) # noqa
except Exception:
pass
@property
def prefix(self) -> str:
return "parallel_request_limiter_v2"
def _get_current_usage_key(
self,
user_api_key_dict: UserAPIKeyAuth,
precise_minute: str,
model: Optional[str],
rate_limit_type: Literal["key", "model_per_key", "user", "customer", "team"],
group: RateLimitGroups,
) -> str:
if rate_limit_type == "key":
return (
f"{self.prefix}::{user_api_key_dict.api_key}::{precise_minute}::{group}"
)
elif rate_limit_type == "model_per_key" and model is not None:
return f"{self.prefix}::{user_api_key_dict.api_key}::{model}::{precise_minute}::{group}"
elif rate_limit_type == "user":
return (
f"{self.prefix}::{user_api_key_dict.user_id}::{precise_minute}::{group}"
)
elif rate_limit_type == "customer":
return f"{self.prefix}::{user_api_key_dict.end_user_id}::{precise_minute}::{group}"
elif rate_limit_type == "team":
return (
f"{self.prefix}::{user_api_key_dict.team_id}::{precise_minute}::{group}"
)
else:
raise ValueError(f"Invalid rate limit type: {rate_limit_type}")
def get_key_pattern_to_sync(self) -> Optional[str]:
return self.prefix + "::"
async def check_key_in_limits_v2(
self,
user_api_key_dict: UserAPIKeyAuth,
data: dict,
max_parallel_requests: int,
precise_minute: str,
tpm_limit: int,
rpm_limit: int,
rate_limit_type: Literal["key", "model_per_key", "user", "customer", "team"],
):
## INCREMENT CURRENT USAGE
increment_list: List[Tuple[str, int]] = []
increment_value_by_group = {
"request_count": 1,
"tpm": 0,
"rpm": 1,
}
for group in ["request_count", "rpm", "tpm"]:
key = self._get_current_usage_key(
user_api_key_dict=user_api_key_dict,
precise_minute=precise_minute,
model=data.get("model", None),
rate_limit_type=rate_limit_type,
group=cast(RateLimitGroups, group),
)
increment_list.append((key, increment_value_by_group[group]))
results = await self._increment_value_list_in_current_window(
increment_list=increment_list,
ttl=60,
)
if (
results[0] > max_parallel_requests
or results[1] > rpm_limit
or results[2] > tpm_limit
):
raise self.raise_rate_limit_error(
additional_details=f"{CommonProxyErrors.max_parallel_request_limit_reached.value}. Hit limit for {rate_limit_type}. Current limits: max_parallel_requests: {max_parallel_requests}, tpm_limit: {tpm_limit}, rpm_limit: {rpm_limit}"
)
def time_to_next_minute(self) -> float:
# Get the current time
now = datetime.now()
# Calculate the next minute
next_minute = (now + timedelta(minutes=1)).replace(second=0, microsecond=0)
# Calculate the difference in seconds
seconds_to_next_minute = (next_minute - now).total_seconds()
return seconds_to_next_minute
def raise_rate_limit_error(
self, additional_details: Optional[str] = None
) -> HTTPException:
"""
Raise an HTTPException with a 429 status code and a retry-after header
"""
error_message = "Max parallel request limit reached"
if additional_details is not None:
error_message = error_message + " " + additional_details
raise HTTPException(
status_code=429,
detail=f"Max parallel request limit reached {additional_details}",
headers={"retry-after": str(self.time_to_next_minute())},
)
async def async_pre_call_hook( # noqa: PLR0915
self,
user_api_key_dict: UserAPIKeyAuth,
cache: DualCache,
data: dict,
call_type: str,
):
self.print_verbose("Inside Max Parallel Request Pre-Call Hook")
api_key = user_api_key_dict.api_key
max_parallel_requests = user_api_key_dict.max_parallel_requests
if max_parallel_requests is None:
max_parallel_requests = sys.maxsize
if data is None:
data = {}
global_max_parallel_requests = data.get("metadata", {}).get(
"global_max_parallel_requests", None
)
tpm_limit = getattr(user_api_key_dict, "tpm_limit", sys.maxsize)
if tpm_limit is None:
tpm_limit = sys.maxsize
rpm_limit = getattr(user_api_key_dict, "rpm_limit", sys.maxsize)
if rpm_limit is None:
rpm_limit = sys.maxsize
# ------------
# Setup values
# ------------
if global_max_parallel_requests is not None:
# get value from cache
_key = "global_max_parallel_requests"
current_global_requests = await self.internal_usage_cache.async_get_cache(
key=_key,
local_only=True,
litellm_parent_otel_span=user_api_key_dict.parent_otel_span,
)
# check if below limit
if current_global_requests is None:
current_global_requests = 1
# if above -> raise error
if current_global_requests >= global_max_parallel_requests:
return self.raise_rate_limit_error(
additional_details=f"Hit Global Limit: Limit={global_max_parallel_requests}, current: {current_global_requests}"
)
# if below -> increment
else:
await self.internal_usage_cache.async_increment_cache(
key=_key,
value=1,
local_only=True,
litellm_parent_otel_span=user_api_key_dict.parent_otel_span,
)
_model = data.get("model", None)
current_date = datetime.now().strftime("%Y-%m-%d")
current_hour = datetime.now().strftime("%H")
current_minute = datetime.now().strftime("%M")
precise_minute = f"{current_date}-{current_hour}-{current_minute}"
if api_key is not None:
# CHECK IF REQUEST ALLOWED for key
await self.check_key_in_limits_v2(
user_api_key_dict=user_api_key_dict,
data=data,
max_parallel_requests=max_parallel_requests,
precise_minute=precise_minute,
tpm_limit=tpm_limit,
rpm_limit=rpm_limit,
rate_limit_type="key",
)
return
async def _update_usage_in_cache_post_call(
self,
user_api_key_dict: UserAPIKeyAuth,
precise_minute: str,
model: Optional[str],
total_tokens: int,
litellm_parent_otel_span: Union[Span, None] = None,
):
increment_list: List[Tuple[str, int]] = []
increment_value_by_group = {
"request_count": -1,
"tpm": total_tokens,
"rpm": 0,
}
for group in ["request_count", "rpm", "tpm"]:
key = self._get_current_usage_key(
user_api_key_dict=user_api_key_dict,
precise_minute=precise_minute,
model=model,
rate_limit_type="key",
group=cast(RateLimitGroups, group),
)
increment_list.append((key, increment_value_by_group[group]))
if increment_list: # Only call if we have values to increment
await self._increment_value_list_in_current_window(
increment_list=increment_list,
ttl=60,
)
async def async_log_success_event( # noqa: PLR0915
self, kwargs, response_obj, start_time, end_time
):
from litellm.proxy.common_utils.callback_utils import (
get_model_group_from_litellm_kwargs,
)
litellm_parent_otel_span: Union[Span, None] = _get_parent_otel_span_from_kwargs(
kwargs=kwargs
)
try:
self.print_verbose("INSIDE parallel request limiter ASYNC SUCCESS LOGGING")
# ------------
# Setup values
# ------------
global_max_parallel_requests = kwargs["litellm_params"]["metadata"].get(
"global_max_parallel_requests", None
)
user_api_key = kwargs["litellm_params"]["metadata"]["user_api_key"]
user_api_key_user_id = kwargs["litellm_params"]["metadata"].get(
"user_api_key_user_id", None
)
user_api_key_team_id = kwargs["litellm_params"]["metadata"].get(
"user_api_key_team_id", None
)
user_api_key_end_user_id = kwargs.get("user")
# ------------
# Setup values
# ------------
if global_max_parallel_requests is not None:
# get value from cache
_key = "global_max_parallel_requests"
# decrement
await self.internal_usage_cache.async_increment_cache(
key=_key,
value=-1,
local_only=True,
litellm_parent_otel_span=litellm_parent_otel_span,
)
current_date = datetime.now().strftime("%Y-%m-%d")
current_hour = datetime.now().strftime("%H")
current_minute = datetime.now().strftime("%M")
precise_minute = f"{current_date}-{current_hour}-{current_minute}"
model_group = get_model_group_from_litellm_kwargs(kwargs)
total_tokens = 0
if isinstance(response_obj, ModelResponse):
total_tokens = response_obj.usage.total_tokens # type: ignore
# ------------
# Update usage - API Key
# ------------
await self._update_usage_in_cache_post_call(
user_api_key_dict=UserAPIKeyAuth(
api_key=user_api_key,
user_id=user_api_key_user_id,
team_id=user_api_key_team_id,
end_user_id=user_api_key_end_user_id,
),
precise_minute=precise_minute,
model=model_group,
total_tokens=total_tokens,
)
except Exception as e:
verbose_proxy_logger.exception(
"Inside Parallel Request Limiter: An exception occurred - {}".format(
str(e)
)
)
async def async_post_call_failure_hook(
self,
request_data: dict,
original_exception: Exception,
user_api_key_dict: UserAPIKeyAuth,
):
try:
self.print_verbose("Inside Max Parallel Request Failure Hook")
model_group = request_data.get("model", None)
current_date = datetime.now().strftime("%Y-%m-%d")
current_hour = datetime.now().strftime("%H")
current_minute = datetime.now().strftime("%M")
precise_minute = f"{current_date}-{current_hour}-{current_minute}"
## decrement call count if call failed
await self._update_usage_in_cache_post_call(
user_api_key_dict=user_api_key_dict,
precise_minute=precise_minute,
model=model_group,
total_tokens=0,
)
except Exception as e:
verbose_proxy_logger.exception(
"Inside Parallel Request Limiter: An exception occurred - {}".format(
str(e)
)
)

1
enterprise/enterprise_hooks/session_handler.py
View File

@ -1,5 +1,4 @@
from litellm.proxy._types import SpendLogsPayload
from litellm.integrations.custom_logger import CustomLogger
from litellm._logging import verbose_proxy_logger
from typing import Optional, List, Union
import json

1
litellm/caching/in_memory_cache.py
View File

@ -183,7 +183,6 @@ class InMemoryCache(BaseCache):
init_value = await self.async_get_cache(key=key) or 0
value = init_value + value
await self.async_set_cache(key, value, **kwargs)
return value
def flush_cache(self):

11
litellm/caching/redis_cache.py
View File

@ -233,14 +233,17 @@ class RedisCache(BaseCache):
raise e
async def async_scan_iter(self, pattern: str, count: int = 100) -> list:
from redis.asyncio import Redis
start_time = time.time()
try:
keys = []
_redis_client: Redis = self.init_async_client() # type: ignore
_redis_client = self.init_async_client()
if not hasattr(_redis_client, "scan_iter"):
verbose_logger.debug(
"Redis client does not support scan_iter, potentially using Redis Cluster. Returning empty list."
)
return []
async for key in _redis_client.scan_iter(match=pattern + "*", count=count):
async for key in _redis_client.scan_iter(match=pattern + "*", count=count): # type: ignore
keys.append(key)
if len(keys) >= count:
break

24
litellm/proxy/hooks/__init__.py
View File

@ -1,4 +1,5 @@
from typing import Literal, Union
import os
from typing import Literal, Type, Union
from . import *
from .cache_control_check import _PROXY_CacheControlCheck
@ -6,11 +7,30 @@ from .managed_files import _PROXY_LiteLLMManagedFiles
from .max_budget_limiter import _PROXY_MaxBudgetLimiter
from .parallel_request_limiter import _PROXY_MaxParallelRequestsHandler
try:
if (
os.getenv("EXPERIMENTAL_MULTI_INSTANCE_RATE_LIMITING", "false").lower()
== "true"
): # FEATURE FLAG as it's still in development
from enterprise.enterprise_hooks.parallel_request_limiter_v2 import (
_PROXY_MaxParallelRequestsHandler as _PROXY_MaxParallelRequestsHandlerV2,
)
max_parallel_request_handler: Type[
Union[
_PROXY_MaxParallelRequestsHandler, _PROXY_MaxParallelRequestsHandlerV2
]
] = _PROXY_MaxParallelRequestsHandlerV2
else:
max_parallel_request_handler = _PROXY_MaxParallelRequestsHandler
except ImportError:
max_parallel_request_handler = _PROXY_MaxParallelRequestsHandler
# List of all available hooks that can be enabled
PROXY_HOOKS = {
"max_budget_limiter": _PROXY_MaxBudgetLimiter,
"managed_files": _PROXY_LiteLLMManagedFiles,
"parallel_request_limiter": _PROXY_MaxParallelRequestsHandler,
"parallel_request_limiter": max_parallel_request_handler,
"cache_control_check": _PROXY_CacheControlCheck,
}

98
litellm/router_strategy/base_routing_strategy.py
View File

@ -3,9 +3,8 @@ Base class across routing strategies to abstract commmon functions like batch in
"""
import asyncio
import threading
from abc import ABC
from typing import List, Optional, Set, Union
from typing import List, Optional, Set, Tuple, Union
from litellm._logging import verbose_router_logger
from litellm.caching.caching import DualCache
@ -22,26 +21,51 @@ class BaseRoutingStrategy(ABC):
):
self.dual_cache = dual_cache
self.redis_increment_operation_queue: List[RedisPipelineIncrementOperation] = []
self._sync_task: Optional[asyncio.Task[None]] = None
if should_batch_redis_writes:
try:
# Try to get existing event loop
loop = asyncio.get_event_loop()
if loop.is_running():
# If loop exists and is running, create task in existing loop
loop.create_task(
self.periodic_sync_in_memory_spend_with_redis(
default_sync_interval=default_sync_interval
)
)
else:
self._create_sync_thread(default_sync_interval)
except RuntimeError: # No event loop in current thread
self._create_sync_thread(default_sync_interval)
self.setup_sync_task(default_sync_interval)
self.in_memory_keys_to_update: set[
str
] = set() # Set with max size of 1000 keys
def setup_sync_task(self, default_sync_interval: Optional[Union[int, float]]):
"""Setup the sync task in a way that's compatible with FastAPI"""
try:
loop = asyncio.get_running_loop()
except RuntimeError:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
self._sync_task = loop.create_task(
self.periodic_sync_in_memory_spend_with_redis(
default_sync_interval=default_sync_interval
)
)
async def cleanup(self):
"""Cleanup method to be called when shutting down"""
if self._sync_task is not None:
self._sync_task.cancel()
try:
await self._sync_task
except asyncio.CancelledError:
pass
async def _increment_value_list_in_current_window(
self, increment_list: List[Tuple[str, int]], ttl: int
) -> List[float]:
"""
Increment a list of values in the current window
"""
results = []
for key, value in increment_list:
result = await self._increment_value_in_current_window(
key=key, value=value, ttl=ttl
)
results.append(result)
return results
async def _increment_value_in_current_window(
self, key: str, value: Union[int, float], ttl: int
):
@ -105,10 +129,8 @@ class BaseRoutingStrategy(ABC):
self.redis_increment_operation_queue,
)
if len(self.redis_increment_operation_queue) > 0:
asyncio.create_task(
self.dual_cache.redis_cache.async_increment_pipeline(
increment_list=self.redis_increment_operation_queue,
)
await self.dual_cache.redis_cache.async_increment_pipeline(
increment_list=self.redis_increment_operation_queue,
)
self.redis_increment_operation_queue = []
@ -122,6 +144,12 @@ class BaseRoutingStrategy(ABC):
def add_to_in_memory_keys_to_update(self, key: str):
self.in_memory_keys_to_update.add(key)
def get_key_pattern_to_sync(self) -> Optional[str]:
"""
Get the key pattern to sync
"""
return None
def get_in_memory_keys_to_update(self) -> Set[str]:
return self.in_memory_keys_to_update
@ -150,9 +178,22 @@ class BaseRoutingStrategy(ABC):
await self._push_in_memory_increments_to_redis()
# 2. Fetch all current provider spend from Redis to update in-memory cache
cache_keys = self.get_in_memory_keys_to_update()
pattern = self.get_key_pattern_to_sync()
cache_keys: Optional[Union[Set[str], List[str]]] = None
if pattern:
cache_keys = await self.dual_cache.redis_cache.async_scan_iter(
pattern=pattern
)
cache_keys_list = list(cache_keys)
if cache_keys is None:
cache_keys = (
self.get_in_memory_keys_to_update()
) # if no pattern OR redis cache does not support scan_iter, use in-memory keys
if isinstance(cache_keys, set):
cache_keys_list = list(cache_keys)
else:
cache_keys_list = cache_keys
# Batch fetch current spend values from Redis
redis_values = await self.dual_cache.redis_cache.async_batch_get_cache(
@ -175,16 +216,3 @@ class BaseRoutingStrategy(ABC):
verbose_router_logger.exception(
f"Error syncing in-memory cache with Redis: {str(e)}"
)
def _create_sync_thread(self, default_sync_interval):
"""Helper method to create a new thread for periodic sync"""
thread = threading.Thread(
target=asyncio.run,
args=(
self.periodic_sync_in_memory_spend_with_redis(
default_sync_interval=default_sync_interval
),
),
daemon=True,
)
thread.start()

63
tests/enterprise/conftest.py Normal file
View File

@ -0,0 +1,63 @@
# conftest.py
import importlib
import os
import sys
import pytest
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
import litellm
@pytest.fixture(scope="function", autouse=True)
def setup_and_teardown():
"""
This fixture reloads litellm before every function. To speed up testing by removing callbacks being chained.
"""
curr_dir = os.getcwd() # Get the current working directory
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the project directory to the system path
import litellm
from litellm import Router
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}")
import asyncio
loop = asyncio.get_event_loop_policy().new_event_loop()
asyncio.set_event_loop(loop)
print(litellm)
# from litellm import Router, completion, aembedding, acompletion, embedding
yield
# Teardown code (executes after the yield point)
loop.close() # Close the loop created earlier
asyncio.set_event_loop(None) # Remove the reference to the loop
def pytest_collection_modifyitems(config, items):
# Separate tests in 'test_amazing_proxy_custom_logger.py' and other tests
custom_logger_tests = [
item for item in items if "custom_logger" in item.parent.name
]
other_tests = [item for item in items if "custom_logger" not in item.parent.name]
# Sort tests based on their names
custom_logger_tests.sort(key=lambda x: x.name)
other_tests.sort(key=lambda x: x.name)
# Reorder the items list
items[:] = custom_logger_tests + other_tests

430
tests/enterprise/enterprise_hooks/test_parallel_request_limiter_v2.py Normal file
View File

@ -0,0 +1,430 @@
"""
Unit Tests for the max parallel request limiter v2 for the proxy
"""
import asyncio
import os
import sys
from datetime import datetime
import pytest
import litellm
from litellm import Router
from litellm.caching.caching import DualCache
from litellm.proxy._types import UserAPIKeyAuth
from litellm.proxy.utils import InternalUsageCache, ProxyLogging, hash_token
from enterprise.enterprise_hooks.parallel_request_limiter_v2 import _PROXY_MaxParallelRequestsHandler
from fastapi import HTTPException
@pytest.mark.asyncio
async def test_normal_router_call_v2(monkeypatch):
"""
Test normal router call with parallel request limiter v2
"""
model_list = [
{
"model_name": "azure-model",
"litellm_params": {
"model": "azure/gpt-turbo",
"api_key": "os.environ/AZURE_FRANCE_API_KEY",
"api_base": "https://openai-france-1234.openai.azure.com",
"rpm": 1440,
},
"model_info": {"id": 1},
},
{
"model_name": "azure-model",
"litellm_params": {
"model": "azure/gpt-35-turbo",
"api_key": "os.environ/AZURE_EUROPE_API_KEY",
"api_base": "https://my-endpoint-europe-berri-992.openai.azure.com",
"rpm": 6,
},
"model_info": {"id": 2},
},
]
router = Router(
model_list=model_list,
set_verbose=False,
num_retries=3,
) # type: ignore
_api_key = "sk-12345"
_api_key = hash_token(_api_key)
user_api_key_dict = UserAPIKeyAuth(api_key=_api_key, max_parallel_requests=1)
local_cache = DualCache()
parallel_request_handler = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(local_cache))
monkeypatch.setattr(litellm, "callbacks", [parallel_request_handler])
await parallel_request_handler.async_pre_call_hook(
user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type=""
)
current_date = datetime.now().strftime("%Y-%m-%d")
current_hour = datetime.now().strftime("%H")
current_minute = datetime.now().strftime("%M")
precise_minute = f"{current_date}-{current_hour}-{current_minute}"
request_count_api_key = parallel_request_handler._get_current_usage_key(
user_api_key_dict=user_api_key_dict,
precise_minute=precise_minute,
model=None,
rate_limit_type="key",
group="request_count",
)
await asyncio.sleep(1)
assert (
parallel_request_handler.internal_usage_cache.get_cache(
key=request_count_api_key
)
== 1
)
# normal call
response = await router.acompletion(
model="azure-model",
messages=[{"role": "user", "content": "Hey, how's it going?"}],
metadata={"user_api_key": _api_key},
mock_response="hello",
)
await asyncio.sleep(1) # success is done in a separate thread
print(f"local_cache in normal call: {local_cache}")
assert (
parallel_request_handler.internal_usage_cache.get_cache(
key=request_count_api_key
)
== 0
)
@pytest.mark.asyncio
async def test_normal_router_call_tpm(monkeypatch):
"""
Test normal router call with parallel request limiter v2
"""
model_list = [
{
"model_name": "azure-model",
"litellm_params": {
"model": "azure/gpt-turbo",
"api_key": "os.environ/AZURE_FRANCE_API_KEY",
"api_base": "https://openai-france-1234.openai.azure.com",
"rpm": 1440,
},
"model_info": {"id": 1},
},
{
"model_name": "azure-model",
"litellm_params": {
"model": "azure/gpt-35-turbo",
"api_key": "os.environ/AZURE_EUROPE_API_KEY",
"api_base": "https://my-endpoint-europe-berri-992.openai.azure.com",
"rpm": 6,
},
"model_info": {"id": 2},
},
]
router = Router(
model_list=model_list,
set_verbose=False,
num_retries=3,
) # type: ignore
_api_key = "sk-12345"
_api_key = hash_token(_api_key)
user_api_key_dict = UserAPIKeyAuth(api_key=_api_key, tpm_limit=10)
local_cache = DualCache()
parallel_request_handler = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(local_cache))
monkeypatch.setattr(litellm, "callbacks", [parallel_request_handler])
await parallel_request_handler.async_pre_call_hook(
user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type=""
)
current_date = datetime.now().strftime("%Y-%m-%d")
current_hour = datetime.now().strftime("%H")
current_minute = datetime.now().strftime("%M")
precise_minute = f"{current_date}-{current_hour}-{current_minute}"
request_count_api_key = parallel_request_handler._get_current_usage_key(
user_api_key_dict=user_api_key_dict,
precise_minute=precise_minute,
model=None,
rate_limit_type="key",
group="tpm",
)
await asyncio.sleep(1)
assert (
parallel_request_handler.internal_usage_cache.get_cache(
key=request_count_api_key
)
== 0
)
# normal call
response = await router.acompletion(
model="azure-model",
messages=[{"role": "user", "content": "Hey, how's it going?"}],
metadata={"user_api_key": _api_key},
mock_response="hello",
)
await asyncio.sleep(1) # success is done in a separate thread
print(f"request_count_api_key: {request_count_api_key}")
assert (
parallel_request_handler.internal_usage_cache.get_cache(
key=request_count_api_key
)
== response.usage.total_tokens
)
@pytest.mark.asyncio
async def test_normal_router_call_rpm(monkeypatch):
"""
Test normal router call with parallel request limiter v2
"""
model_list = [
{
"model_name": "azure-model",
"litellm_params": {
"model": "azure/gpt-turbo",
"api_key": "os.environ/AZURE_FRANCE_API_KEY",
"api_base": "https://openai-france-1234.openai.azure.com",
"rpm": 1440,
},
"model_info": {"id": 1},
},
{
"model_name": "azure-model",
"litellm_params": {
"model": "azure/gpt-35-turbo",
"api_key": "os.environ/AZURE_EUROPE_API_KEY",
"api_base": "https://my-endpoint-europe-berri-992.openai.azure.com",
"rpm": 6,
},
"model_info": {"id": 2},
},
]
router = Router(
model_list=model_list,
set_verbose=False,
num_retries=3,
) # type: ignore
_api_key = "sk-12345"
_api_key = hash_token(_api_key)
user_api_key_dict = UserAPIKeyAuth(api_key=_api_key, tpm_limit=10)
local_cache = DualCache()
parallel_request_handler = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(local_cache))
monkeypatch.setattr(litellm, "callbacks", [parallel_request_handler])
await parallel_request_handler.async_pre_call_hook(
user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type=""
)
current_date = datetime.now().strftime("%Y-%m-%d")
current_hour = datetime.now().strftime("%H")
current_minute = datetime.now().strftime("%M")
precise_minute = f"{current_date}-{current_hour}-{current_minute}"
request_count_api_key = parallel_request_handler._get_current_usage_key(
user_api_key_dict=user_api_key_dict,
precise_minute=precise_minute,
model=None,
rate_limit_type="key",
group="rpm",
)
await asyncio.sleep(1)
assert (
parallel_request_handler.internal_usage_cache.get_cache(
key=request_count_api_key
)
== 1
)
# normal call
response = await router.acompletion(
model="azure-model",
messages=[{"role": "user", "content": "Hey, how's it going?"}],
metadata={"user_api_key": _api_key},
mock_response="hello",
)
await asyncio.sleep(1) # success is done in a separate thread
print(f"request_count_api_key: {request_count_api_key}")
assert (
parallel_request_handler.internal_usage_cache.get_cache(
key=request_count_api_key
)
== 1
)
with pytest.raises(HTTPException):
await parallel_request_handler.async_pre_call_hook(
user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type=""
)
@pytest.mark.asyncio
async def test_streaming_router_call_v2(monkeypatch):
"""
Test streaming router call with parallel request limiter v2
"""
model_list = [
{
"model_name": "azure-model",
"litellm_params": {
"model": "azure/gpt-turbo",
"api_key": "os.environ/AZURE_FRANCE_API_KEY",
"api_base": "https://openai-france-1234.openai.azure.com",
"rpm": 1440,
},
"model_info": {"id": 1},
},
{
"model_name": "azure-model",
"litellm_params": {
"model": "azure/gpt-35-turbo",
"api_key": "os.environ/AZURE_EUROPE_API_KEY",
"api_base": "https://my-endpoint-europe-berri-992.openai.azure.com",
"rpm": 6,
},
"model_info": {"id": 2},
},
]
router = Router(
model_list=model_list,
set_verbose=False,
num_retries=3,
) # type: ignore
_api_key = "sk-12345"
_api_key = hash_token(_api_key)
user_api_key_dict = UserAPIKeyAuth(api_key=_api_key, max_parallel_requests=1)
local_cache = DualCache()
print(f"litellm callbacks pre-set: {litellm.callbacks}")
parallel_request_handler = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(local_cache))
monkeypatch.setattr(litellm, "callbacks", [parallel_request_handler])
await parallel_request_handler.async_pre_call_hook(
user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type=""
)
current_date = datetime.now().strftime("%Y-%m-%d")
current_hour = datetime.now().strftime("%H")
current_minute = datetime.now().strftime("%M")
precise_minute = f"{current_date}-{current_hour}-{current_minute}"
request_count_api_key = parallel_request_handler._get_current_usage_key(
user_api_key_dict=user_api_key_dict,
precise_minute=precise_minute,
model=None,
rate_limit_type="key",
group="request_count",
)
await asyncio.sleep(1)
assert (
parallel_request_handler.internal_usage_cache.get_cache(
key=request_count_api_key
)
== 1
)
# streaming call
print(f"litellm callbacks: {litellm.callbacks}")
response = await router.acompletion(
model="azure-model",
messages=[{"role": "user", "content": "Hey, how's it going?"}],
stream=True,
metadata={"user_api_key": _api_key},
mock_response="hello",
)
async for chunk in response:
continue
await asyncio.sleep(3) # success is done in a separate thread
print(f"local_cache in streaming call: {local_cache}")
assert (
parallel_request_handler.internal_usage_cache.get_cache(
key=request_count_api_key
)
== 0
)
@pytest.mark.asyncio
async def test_bad_router_call_v2(monkeypatch):
"""
Test bad router call with parallel request limiter v2
"""
model_list = [
{
"model_name": "azure-model",
"litellm_params": {
"model": "azure/gpt-turbo",
"api_key": "os.environ/AZURE_FRANCE_API_KEY",
"api_base": "https://openai-france-1234.openai.azure.com",
"rpm": 1440,
},
"model_info": {"id": 1},
},
{
"model_name": "azure-model",
"litellm_params": {
"model": "azure/gpt-35-turbo",
"api_key": "os.environ/AZURE_EUROPE_API_KEY",
"api_base": "https://my-endpoint-europe-berri-992.openai.azure.com",
"rpm": 6,
},
"model_info": {"id": 2},
},
]
router = Router(
model_list=model_list,
set_verbose=False,
num_retries=3,
) # type: ignore
_api_key = "sk-12345"
_api_key = hash_token(_api_key)
user_api_key_dict = UserAPIKeyAuth(api_key=_api_key, max_parallel_requests=1)
local_cache = DualCache()
parallel_request_handler = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(local_cache))
monkeypatch.setattr(litellm, "callbacks", [parallel_request_handler])
await parallel_request_handler.async_pre_call_hook(
user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type=""
)
current_date = datetime.now().strftime("%Y-%m-%d")
current_hour = datetime.now().strftime("%H")
current_minute = datetime.now().strftime("%M")
precise_minute = f"{current_date}-{current_hour}-{current_minute}"
request_count_api_key = parallel_request_handler._get_current_usage_key(
user_api_key_dict=user_api_key_dict,
precise_minute=precise_minute,
model=None,
rate_limit_type="key",
group="request_count",
)
await asyncio.sleep(1)
assert (
parallel_request_handler.internal_usage_cache.get_cache(
key=request_count_api_key
)
== 1
)
# bad streaming call
await parallel_request_handler.async_post_call_failure_hook(
request_data={},
original_exception=Exception("test"),
user_api_key_dict=user_api_key_dict,
)
assert (
parallel_request_handler.internal_usage_cache.get_cache(
key=request_count_api_key
)
== 0
)

3
tests/local_testing/test_text_completion.py
View File

@ -3890,6 +3890,9 @@ def test_text_completion_basic():
# print(response.choices[0].text)
response_str = response["choices"][0]["text"]
except Exception as e:
if "502: Bad gateway" in str(e):
print("502: Bad gateway error occurred... passing")
return
pytest.fail(f"Error occurred: {e}")

2
tests/proxy_unit_tests/test_key_generate_prisma.py
View File

@ -1373,7 +1373,7 @@ def test_generate_and_update_key(prisma_client):
# Check that budget_reset_at is on the first day of next month
next_month_first_day = end_of_month
# Assert that the reset date is the 1st of next month (0 or 1 day difference)
assert abs((budget_reset_at - next_month_first_day).days) <= 1
assert abs((next_month_first_day - budget_reset_at).days) <= 1
# cleanup - delete key
delete_key_request = KeyRequest(keys=[generated_key])