litellm/litellm/router_strategy/provider_budgets.py
2024-11-24 09:45:33 -08:00

367 lines
14 KiB
Python

"""
Provider budget limiting
Use this if you want to set $ budget limits for each provider.
Note: This is a filter, like tag-routing. Meaning it will accept healthy deployments and then filter out deployments that have exceeded their budget limit.
This means you can use this with weighted-pick, lowest-latency, simple-shuffle, routing etc
Example:
```
openai:
budget_limit: 0.000000000001
time_period: 1d
anthropic:
budget_limit: 100
time_period: 7d
```
"""
import asyncio
from typing import TYPE_CHECKING, Any, Dict, List, Optional, TypedDict, Union
import litellm
from litellm._logging import verbose_router_logger
from litellm.caching.caching import DualCache
from litellm.caching.redis_cache import RedisPipelineIncrementOperation
from litellm.integrations.custom_logger import CustomLogger
from litellm.litellm_core_utils.core_helpers import _get_parent_otel_span_from_kwargs
from litellm.litellm_core_utils.duration_parser import duration_in_seconds
from litellm.router_utils.cooldown_callbacks import (
_get_prometheus_logger_from_callbacks,
)
from litellm.types.router import (
LiteLLM_Params,
ProviderBudgetConfigType,
ProviderBudgetInfo,
RouterErrors,
)
from litellm.types.utils import StandardLoggingPayload
if TYPE_CHECKING:
from opentelemetry.trace import Span as _Span
Span = _Span
else:
Span = Any
DEFAULT_REDIS_SYNC_INTERVAL = 60
class ProviderBudgetLimiting(CustomLogger):
def __init__(self, router_cache: DualCache, provider_budget_config: dict):
self.router_cache = router_cache
self.redis_increment_operation_queue: List[RedisPipelineIncrementOperation] = []
asyncio.create_task(self.periodic_sync_in_memory_spend_with_redis())
# cast elements of provider_budget_config to ProviderBudgetInfo
for provider, config in provider_budget_config.items():
if config is None:
raise ValueError(
f"No budget config found for provider {provider}, provider_budget_config: {provider_budget_config}"
)
if not isinstance(config, ProviderBudgetInfo):
provider_budget_config[provider] = ProviderBudgetInfo(
budget_limit=config.get("budget_limit"),
time_period=config.get("time_period"),
)
self.provider_budget_config: ProviderBudgetConfigType = provider_budget_config
verbose_router_logger.debug(
f"Initalized Provider budget config: {self.provider_budget_config}"
)
# Add self to litellm callbacks if it's a list
if isinstance(litellm.callbacks, list):
litellm.callbacks.append(self) # type: ignore
async def async_filter_deployments(
self,
healthy_deployments: Union[List[Dict[str, Any]], Dict[str, Any]],
request_kwargs: Optional[Dict] = None,
):
"""
Filter out deployments that have exceeded their provider budget limit.
Example:
if deployment = openai/gpt-3.5-turbo
and openai spend > openai budget limit
then skip this deployment
"""
# If a single deployment is passed, convert it to a list
if isinstance(healthy_deployments, dict):
healthy_deployments = [healthy_deployments]
# Don't do any filtering if there are no healthy deployments
if len(healthy_deployments) == 0:
return healthy_deployments
potential_deployments: List[Dict] = []
# Extract the parent OpenTelemetry span for tracing
parent_otel_span: Optional[Span] = _get_parent_otel_span_from_kwargs(
request_kwargs
)
# Collect all providers and their budget configs
# {"openai": ProviderBudgetInfo, "anthropic": ProviderBudgetInfo, "azure": None}
_provider_configs: Dict[str, Optional[ProviderBudgetInfo]] = {}
for deployment in healthy_deployments:
provider = self._get_llm_provider_for_deployment(deployment)
if provider is None:
continue
budget_config = self._get_budget_config_for_provider(provider)
_provider_configs[provider] = budget_config
# Filter out providers without budget config
provider_configs: Dict[str, ProviderBudgetInfo] = {
provider: config
for provider, config in _provider_configs.items()
if config is not None
}
# Build cache keys for batch retrieval
cache_keys = []
for provider, config in provider_configs.items():
cache_keys.append(f"provider_spend:{provider}:{config.time_period}")
# Fetch current spend for all providers using batch cache
_current_spends = await self.router_cache.async_batch_get_cache(
keys=cache_keys,
parent_otel_span=parent_otel_span,
)
current_spends: List = _current_spends or [0.0] * len(provider_configs)
# Map providers to their current spend values
provider_spend_map: Dict[str, float] = {}
for idx, provider in enumerate(provider_configs.keys()):
provider_spend_map[provider] = float(current_spends[idx] or 0.0)
# Filter healthy deployments based on budget constraints
deployment_above_budget_info: str = "" # used to return in error message
for deployment in healthy_deployments:
provider = self._get_llm_provider_for_deployment(deployment)
if provider is None:
continue
budget_config = provider_configs.get(provider)
if not budget_config:
continue
current_spend = provider_spend_map.get(provider, 0.0)
budget_limit = budget_config.budget_limit
verbose_router_logger.debug(
f"Current spend for {provider}: {current_spend}, budget limit: {budget_limit}"
)
self._track_provider_remaining_budget_prometheus(
provider=provider,
spend=current_spend,
budget_limit=budget_limit,
)
if current_spend >= budget_limit:
debug_msg = f"Exceeded budget for provider {provider}: {current_spend} >= {budget_limit}"
verbose_router_logger.debug(debug_msg)
deployment_above_budget_info += f"{debug_msg}\n"
continue
potential_deployments.append(deployment)
if len(potential_deployments) == 0:
raise ValueError(
f"{RouterErrors.no_deployments_with_provider_budget_routing.value}: {deployment_above_budget_info}"
)
return potential_deployments
async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
"""
Increment provider spend in DualCache (InMemory + Redis)
Handles saving current provider spend to Redis.
Spend is stored as:
provider_spend:{provider}:{time_period}
ex. provider_spend:openai:1d
ex. provider_spend:anthropic:7d
The time period is tracked for time_periods set in the provider budget config.
"""
verbose_router_logger.debug("in ProviderBudgetLimiting.async_log_success_event")
standard_logging_payload: Optional[StandardLoggingPayload] = kwargs.get(
"standard_logging_object", None
)
if standard_logging_payload is None:
raise ValueError("standard_logging_payload is required")
response_cost: float = standard_logging_payload.get("response_cost", 0)
custom_llm_provider: str = kwargs.get("litellm_params", {}).get(
"custom_llm_provider", None
)
if custom_llm_provider is None:
raise ValueError("custom_llm_provider is required")
budget_config = self._get_budget_config_for_provider(custom_llm_provider)
if budget_config is None:
raise ValueError(
f"No budget config found for provider {custom_llm_provider}, self.provider_budget_config: {self.provider_budget_config}"
)
spend_key = f"provider_spend:{custom_llm_provider}:{budget_config.time_period}"
ttl_seconds = duration_in_seconds(duration=budget_config.time_period)
# Create RedisPipelineIncrementOperation object
increment_op = RedisPipelineIncrementOperation(
key=spend_key, increment_value=response_cost, ttl_seconds=ttl_seconds
)
await self.router_cache.in_memory_cache.async_increment(
key=spend_key,
value=response_cost,
)
self.redis_increment_operation_queue.append(increment_op)
verbose_router_logger.debug(
f"Incremented spend for {spend_key} by {response_cost}, ttl: {ttl_seconds}"
)
async def periodic_sync_in_memory_spend_with_redis(self):
"""
Handler that triggers sync_in_memory_spend_with_redis every DEFAULT_REDIS_SYNC_INTERVAL seconds
Required for multi-instance environment usage of provider budgets
"""
while True:
try:
await self._sync_in_memory_spend_with_redis()
await asyncio.sleep(
DEFAULT_REDIS_SYNC_INTERVAL
) # Wait for 5 seconds before next sync
except Exception as e:
verbose_router_logger.error(f"Error in periodic sync task: {str(e)}")
await asyncio.sleep(
DEFAULT_REDIS_SYNC_INTERVAL
) # Still wait 5 seconds on error before retrying
async def _push_in_memory_increments_to_redis(self):
"""
This is a latency / speed optimization.
How this works:
- Collect all provider spend increments in `router_cache.in_memory_cache`, done in async_log_success_event
- Push all increments to Redis in this function
- Reset the in-memory `last_synced_values`
"""
try:
if not self.router_cache.redis_cache:
return # Redis is not initialized
verbose_router_logger.debug(
"Pushing Redis Increment Pipeline for queue: %s",
self.redis_increment_operation_queue,
)
if len(self.redis_increment_operation_queue) > 0:
asyncio.create_task(
self.router_cache.redis_cache.async_increment_pipeline(
increment_list=self.redis_increment_operation_queue,
)
)
self.redis_increment_operation_queue = []
except Exception as e:
verbose_router_logger.error(
f"Error syncing in-memory cache with Redis: {str(e)}"
)
async def _sync_in_memory_spend_with_redis(self):
"""
Ensures in-memory cache is updated with latest Redis values for all provider spends.
Why Do we need this?
- Redis is our source of truth for provider spend
- Optimization to hit ~100ms latency. Performance was impacted when redis was used for read/write per request
In a multi-instance evironment, each instance needs to periodically get the provider spend from Redis to ensure it is consistent across all instances.
"""
try:
# No need to sync if Redis cache is not initialized
if self.router_cache.redis_cache is None:
return
# Push all provider spend increments to Redis
await self._push_in_memory_increments_to_redis()
# Handle Reading all current provider spend from Redis in Memory
# Get all providers and their budget configs
cache_keys = []
for provider, config in self.provider_budget_config.items():
if config is None:
continue
cache_keys.append(f"provider_spend:{provider}:{config.time_period}")
# Batch fetch current spend values from Redis
redis_values = await self.router_cache.redis_cache.async_batch_get_cache(
key_list=cache_keys
)
# Update in-memory cache with Redis values
if isinstance(redis_values, dict): # Check if redis_values is a dictionary
for key, value in redis_values.items():
if value is not None:
await self.router_cache.in_memory_cache.async_set_cache(
key=key, value=float(value)
)
verbose_router_logger.debug(
f"Updated in-memory cache for {key}: {value}"
)
except Exception as e:
verbose_router_logger.error(
f"Error syncing in-memory cache with Redis: {str(e)}"
)
def _get_budget_config_for_provider(
self, provider: str
) -> Optional[ProviderBudgetInfo]:
return self.provider_budget_config.get(provider, None)
def _get_llm_provider_for_deployment(self, deployment: Dict) -> Optional[str]:
try:
_litellm_params: LiteLLM_Params = LiteLLM_Params(
**deployment.get("litellm_params", {"model": ""})
)
_, custom_llm_provider, _, _ = litellm.get_llm_provider(
model=_litellm_params.model,
litellm_params=_litellm_params,
)
except Exception:
verbose_router_logger.error(
f"Error getting LLM provider for deployment: {deployment}"
)
return None
return custom_llm_provider
def _track_provider_remaining_budget_prometheus(
self, provider: str, spend: float, budget_limit: float
):
"""
Optional helper - emit provider remaining budget metric to Prometheus
This is helpful for debugging and monitoring provider budget limits.
"""
from litellm.integrations.prometheus import PrometheusLogger
prometheus_logger = _get_prometheus_logger_from_callbacks()
if prometheus_logger:
prometheus_logger.track_provider_remaining_budget(
provider=provider,
spend=spend,
budget_limit=budget_limit,
)