litellm-mirror/litellm/router_utils/pattern_match_deployments.py
Krish Dholakia 1cd1d23fdf
LiteLLM Minor Fixes & Improvements (10/23/2024) (#6407)
* docs(bedrock.md): clarify bedrock auth in litellm docs

* fix(convert_dict_to_response.py): Fixes https://github.com/BerriAI/litellm/issues/6387

* feat(pattern_match_deployments.py): more robust handling for wildcard routes (model_name: custom_route/* -> openai/*)

Enables user to expose custom routes to users with dynamic handling

* test: add more testing

* docs(custom_pricing.md): add debug tutorial for custom pricing

* test: skip codestral test - unreachable backend

* test: fix test

* fix(pattern_matching_deployments.py): fix typing

* test: cleanup codestral tests - backend api unavailable

* (refactor) prometheus async_log_success_event to be under 100 LOC  (#6416)

* unit testig for prometheus

* unit testing for success metrics

* use 1 helper for _increment_token_metrics

* use helper for _increment_remaining_budget_metrics

* use _increment_remaining_budget_metrics

* use _increment_top_level_request_and_spend_metrics

* use helper for _set_latency_metrics

* remove noqa violation

* fix test prometheus

* test prometheus

* unit testing for all prometheus helper functions

* fix prom unit tests

* fix unit tests prometheus

* fix unit test prom

* (refactor) router - use static methods for client init utils  (#6420)

* use InitalizeOpenAISDKClient

* use InitalizeOpenAISDKClient static method

* fix  # noqa: PLR0915

* (code cleanup) remove unused and undocumented logging integrations - litedebugger, berrispend  (#6406)

* code cleanup remove unused and undocumented code files

* fix unused logging integrations cleanup

* bump: version 1.50.3 → 1.50.4

---------

Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
2024-10-24 19:01:41 -07:00

183 lines
5.9 KiB
Python

"""
Class to handle llm wildcard routing and regex pattern matching
"""
import copy
import re
from re import Match
from typing import Dict, List, Optional
from litellm import get_llm_provider
from litellm._logging import verbose_router_logger
class PatternMatchRouter:
"""
Class to handle llm wildcard routing and regex pattern matching
doc: https://docs.litellm.ai/docs/proxy/configs#provider-specific-wildcard-routing
This class will store a mapping for regex pattern: List[Deployments]
"""
def __init__(self):
self.patterns: Dict[str, List] = {}
def add_pattern(self, pattern: str, llm_deployment: Dict):
"""
Add a regex pattern and the corresponding llm deployments to the patterns
Args:
pattern: str
llm_deployment: str or List[str]
"""
# Convert the pattern to a regex
regex = self._pattern_to_regex(pattern)
if regex not in self.patterns:
self.patterns[regex] = []
self.patterns[regex].append(llm_deployment)
def _pattern_to_regex(self, pattern: str) -> str:
"""
Convert a wildcard pattern to a regex pattern
example:
pattern: openai/*
regex: openai/.*
pattern: openai/fo::*::static::*
regex: openai/fo::.*::static::.*
Args:
pattern: str
Returns:
str: regex pattern
"""
# # Replace '*' with '.*' for regex matching
# regex = pattern.replace("*", ".*")
# # Escape other special characters
# regex = re.escape(regex).replace(r"\.\*", ".*")
# return f"^{regex}$"
return re.escape(pattern).replace(r"\*", "(.*)")
def route(self, request: Optional[str]) -> Optional[List[Dict]]:
"""
Route a requested model to the corresponding llm deployments based on the regex pattern
loop through all the patterns and find the matching pattern
if a pattern is found, return the corresponding llm deployments
if no pattern is found, return None
Args:
request: Optional[str]
Returns:
Optional[List[Deployment]]: llm deployments
"""
try:
if request is None:
return None
for pattern, llm_deployments in self.patterns.items():
if re.match(pattern, request):
return llm_deployments
except Exception as e:
verbose_router_logger.debug(f"Error in PatternMatchRouter.route: {str(e)}")
return None # No matching pattern found
@staticmethod
def set_deployment_model_name(
matched_pattern: Match,
litellm_deployment_litellm_model: str,
) -> str:
"""
Set the model name for the matched pattern llm deployment
E.g.:
model_name: llmengine/* (can be any regex pattern or wildcard pattern)
litellm_params:
model: openai/*
if model_name = "llmengine/foo" -> model = "openai/foo"
"""
## BASE CASE: if the deployment model name does not contain a wildcard, return the deployment model name
if "*" not in litellm_deployment_litellm_model:
return litellm_deployment_litellm_model
wildcard_count = litellm_deployment_litellm_model.count("*")
# Extract all dynamic segments from the request
dynamic_segments = matched_pattern.groups()
if len(dynamic_segments) > wildcard_count:
raise ValueError(
f"More wildcards in the deployment model name than the pattern. Wildcard count: {wildcard_count}, dynamic segments count: {len(dynamic_segments)}"
)
# Replace the corresponding wildcards in the litellm model pattern with extracted segments
for segment in dynamic_segments:
litellm_deployment_litellm_model = litellm_deployment_litellm_model.replace(
"*", segment, 1
)
return litellm_deployment_litellm_model
def get_pattern(
self, model: str, custom_llm_provider: Optional[str] = None
) -> Optional[List[Dict]]:
"""
Check if a pattern exists for the given model and custom llm provider
Args:
model: str
custom_llm_provider: Optional[str]
Returns:
bool: True if pattern exists, False otherwise
"""
if custom_llm_provider is None:
try:
(
_,
custom_llm_provider,
_,
_,
) = get_llm_provider(model=model)
except Exception:
# get_llm_provider raises exception when provider is unknown
pass
return self.route(model) or self.route(f"{custom_llm_provider}/{model}")
def get_deployments_by_pattern(
self, model: str, custom_llm_provider: Optional[str] = None
) -> List[Dict]:
"""
Get the deployments by pattern
Args:
model: str
custom_llm_provider: Optional[str]
Returns:
List[Dict]: llm deployments matching the pattern
"""
pattern_match = self.get_pattern(model, custom_llm_provider)
if pattern_match:
provider_deployments = []
for deployment in pattern_match:
dep = copy.deepcopy(deployment)
dep["litellm_params"]["model"] = model
provider_deployments.append(dep)
return provider_deployments
return []
# Example usage:
# router = PatternRouter()
# router.add_pattern('openai/*', [Deployment(), Deployment()])
# router.add_pattern('openai/fo::*::static::*', Deployment())
# print(router.route('openai/gpt-4')) # Output: [Deployment(), Deployment()]
# print(router.route('openai/fo::hi::static::hi')) # Output: [Deployment()]
# print(router.route('something/else')) # Output: None