forked from phoenix/litellm-mirror
4d1b4beb3d
* use folder for caching * fix importing caching * fix clickhouse pyright * fix linting * fix correctly pass kwargs and args * fix test case for embedding * fix linting * fix embedding caching logic * fix refactor handle utils.py * fix test_embedding_caching_azure_individual_items_reordered
523 lines
20 KiB
Python
523 lines
20 KiB
Python
#### What this does ####
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# picks based on response time (for streaming, this is time to first token)
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import random
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import traceback
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from datetime import datetime, timedelta
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from typing import Dict, List, Optional, Union
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from pydantic import BaseModel
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import litellm
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from litellm import ModelResponse, token_counter, verbose_logger
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from litellm.caching.caching import DualCache
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from litellm.integrations.custom_logger import CustomLogger
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class LiteLLMBase(BaseModel):
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"""
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Implements default functions, all pydantic objects should have.
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"""
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def json(self, **kwargs): # type: ignore
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try:
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return self.model_dump() # noqa
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except Exception:
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# if using pydantic v1
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return self.dict()
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class RoutingArgs(LiteLLMBase):
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ttl: float = 1 * 60 * 60 # 1 hour
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lowest_latency_buffer: float = 0
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max_latency_list_size: int = 10
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class LowestLatencyLoggingHandler(CustomLogger):
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test_flag: bool = False
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logged_success: int = 0
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logged_failure: int = 0
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def __init__(
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self, router_cache: DualCache, model_list: list, routing_args: dict = {}
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):
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self.router_cache = router_cache
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self.model_list = model_list
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self.routing_args = RoutingArgs(**routing_args)
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def log_success_event(self, kwargs, response_obj, start_time, end_time):
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try:
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"""
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Update latency usage on success
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"""
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if kwargs["litellm_params"].get("metadata") is None:
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pass
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else:
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model_group = kwargs["litellm_params"]["metadata"].get(
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"model_group", None
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)
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id = kwargs["litellm_params"].get("model_info", {}).get("id", None)
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if model_group is None or id is None:
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return
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elif isinstance(id, int):
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id = str(id)
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# ------------
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# Setup values
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# ------------
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"""
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{
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{model_group}_map: {
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id: {
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"latency": [..]
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f"{date:hour:minute}" : {"tpm": 34, "rpm": 3}
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}
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}
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}
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"""
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latency_key = f"{model_group}_map"
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current_date = datetime.now().strftime("%Y-%m-%d")
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current_hour = datetime.now().strftime("%H")
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current_minute = datetime.now().strftime("%M")
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precise_minute = f"{current_date}-{current_hour}-{current_minute}"
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response_ms: timedelta = end_time - start_time
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time_to_first_token_response_time: Optional[timedelta] = None
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if kwargs.get("stream", None) is not None and kwargs["stream"] is True:
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# only log ttft for streaming request
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time_to_first_token_response_time = (
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kwargs.get("completion_start_time", end_time) - start_time
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)
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final_value: Union[float, timedelta] = response_ms
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time_to_first_token: Optional[float] = None
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total_tokens = 0
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if isinstance(response_obj, ModelResponse):
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_usage = getattr(response_obj, "usage", None)
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if _usage is not None:
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completion_tokens = _usage.completion_tokens
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total_tokens = _usage.total_tokens
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final_value = float(
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response_ms.total_seconds() / completion_tokens
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)
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if time_to_first_token_response_time is not None:
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time_to_first_token = float(
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time_to_first_token_response_time.total_seconds()
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/ completion_tokens
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)
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# ------------
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# Update usage
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# ------------
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request_count_dict = self.router_cache.get_cache(key=latency_key) or {}
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if id not in request_count_dict:
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request_count_dict[id] = {}
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## Latency
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if (
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len(request_count_dict[id].get("latency", []))
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< self.routing_args.max_latency_list_size
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):
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request_count_dict[id].setdefault("latency", []).append(final_value)
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else:
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request_count_dict[id]["latency"] = request_count_dict[id][
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"latency"
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][: self.routing_args.max_latency_list_size - 1] + [final_value]
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## Time to first token
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if time_to_first_token is not None:
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if (
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len(request_count_dict[id].get("time_to_first_token", []))
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< self.routing_args.max_latency_list_size
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):
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request_count_dict[id].setdefault(
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"time_to_first_token", []
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).append(time_to_first_token)
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else:
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request_count_dict[id][
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"time_to_first_token"
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] = request_count_dict[id]["time_to_first_token"][
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: self.routing_args.max_latency_list_size - 1
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] + [
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time_to_first_token
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]
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if precise_minute not in request_count_dict[id]:
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request_count_dict[id][precise_minute] = {}
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## TPM
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request_count_dict[id][precise_minute]["tpm"] = (
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request_count_dict[id][precise_minute].get("tpm", 0) + total_tokens
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)
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## RPM
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request_count_dict[id][precise_minute]["rpm"] = (
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request_count_dict[id][precise_minute].get("rpm", 0) + 1
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)
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self.router_cache.set_cache(
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key=latency_key, value=request_count_dict, ttl=self.routing_args.ttl
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) # reset map within window
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### TESTING ###
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if self.test_flag:
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self.logged_success += 1
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except Exception as e:
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verbose_logger.exception(
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"litellm.proxy.hooks.prompt_injection_detection.py::async_pre_call_hook(): Exception occured - {}".format(
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str(e)
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)
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)
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pass
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async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time):
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"""
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Check if Timeout Error, if timeout set deployment latency -> 100
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"""
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try:
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_exception = kwargs.get("exception", None)
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if isinstance(_exception, litellm.Timeout):
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if kwargs["litellm_params"].get("metadata") is None:
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pass
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else:
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model_group = kwargs["litellm_params"]["metadata"].get(
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"model_group", None
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)
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id = kwargs["litellm_params"].get("model_info", {}).get("id", None)
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if model_group is None or id is None:
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return
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elif isinstance(id, int):
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id = str(id)
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# ------------
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# Setup values
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# ------------
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"""
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{
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{model_group}_map: {
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id: {
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"latency": [..]
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f"{date:hour:minute}" : {"tpm": 34, "rpm": 3}
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}
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}
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}
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"""
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latency_key = f"{model_group}_map"
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request_count_dict = (
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self.router_cache.get_cache(key=latency_key) or {}
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)
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if id not in request_count_dict:
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request_count_dict[id] = {}
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## Latency - give 1000s penalty for failing
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if (
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len(request_count_dict[id].get("latency", []))
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< self.routing_args.max_latency_list_size
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):
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request_count_dict[id].setdefault("latency", []).append(1000.0)
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else:
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request_count_dict[id]["latency"] = request_count_dict[id][
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"latency"
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][: self.routing_args.max_latency_list_size - 1] + [1000.0]
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self.router_cache.set_cache(
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key=latency_key,
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value=request_count_dict,
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ttl=self.routing_args.ttl,
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) # reset map within window
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else:
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# do nothing if it's not a timeout error
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return
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except Exception as e:
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verbose_logger.exception(
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"litellm.proxy.hooks.prompt_injection_detection.py::async_pre_call_hook(): Exception occured - {}".format(
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str(e)
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)
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)
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pass
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async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
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try:
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"""
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Update latency usage on success
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"""
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if kwargs["litellm_params"].get("metadata") is None:
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pass
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else:
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model_group = kwargs["litellm_params"]["metadata"].get(
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"model_group", None
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)
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id = kwargs["litellm_params"].get("model_info", {}).get("id", None)
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if model_group is None or id is None:
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return
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elif isinstance(id, int):
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id = str(id)
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# ------------
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# Setup values
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# ------------
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"""
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{
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{model_group}_map: {
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id: {
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"latency": [..]
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"time_to_first_token": [..]
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f"{date:hour:minute}" : {"tpm": 34, "rpm": 3}
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}
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}
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}
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"""
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latency_key = f"{model_group}_map"
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current_date = datetime.now().strftime("%Y-%m-%d")
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current_hour = datetime.now().strftime("%H")
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current_minute = datetime.now().strftime("%M")
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precise_minute = f"{current_date}-{current_hour}-{current_minute}"
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response_ms: timedelta = end_time - start_time
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time_to_first_token_response_time: Optional[timedelta] = None
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if kwargs.get("stream", None) is not None and kwargs["stream"] is True:
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# only log ttft for streaming request
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time_to_first_token_response_time = (
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kwargs.get("completion_start_time", end_time) - start_time
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)
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final_value: Union[float, timedelta] = response_ms
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total_tokens = 0
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time_to_first_token: Optional[float] = None
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if isinstance(response_obj, ModelResponse):
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_usage = getattr(response_obj, "usage", None)
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if _usage is not None:
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completion_tokens = _usage.completion_tokens
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total_tokens = _usage.total_tokens
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final_value = float(
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response_ms.total_seconds() / completion_tokens
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)
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if time_to_first_token_response_time is not None:
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time_to_first_token = float(
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time_to_first_token_response_time.total_seconds()
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/ completion_tokens
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)
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# ------------
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# Update usage
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# ------------
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request_count_dict = self.router_cache.get_cache(key=latency_key) or {}
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if id not in request_count_dict:
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request_count_dict[id] = {}
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## Latency
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if (
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len(request_count_dict[id].get("latency", []))
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< self.routing_args.max_latency_list_size
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):
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request_count_dict[id].setdefault("latency", []).append(final_value)
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else:
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request_count_dict[id]["latency"] = request_count_dict[id][
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"latency"
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][: self.routing_args.max_latency_list_size - 1] + [final_value]
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## Time to first token
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if time_to_first_token is not None:
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if (
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len(request_count_dict[id].get("time_to_first_token", []))
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< self.routing_args.max_latency_list_size
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):
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request_count_dict[id].setdefault(
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"time_to_first_token", []
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).append(time_to_first_token)
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else:
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request_count_dict[id][
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"time_to_first_token"
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] = request_count_dict[id]["time_to_first_token"][
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: self.routing_args.max_latency_list_size - 1
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] + [
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time_to_first_token
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]
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if precise_minute not in request_count_dict[id]:
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request_count_dict[id][precise_minute] = {}
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## TPM
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request_count_dict[id][precise_minute]["tpm"] = (
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request_count_dict[id][precise_minute].get("tpm", 0) + total_tokens
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)
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## RPM
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request_count_dict[id][precise_minute]["rpm"] = (
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request_count_dict[id][precise_minute].get("rpm", 0) + 1
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)
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self.router_cache.set_cache(
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key=latency_key, value=request_count_dict, ttl=self.routing_args.ttl
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) # reset map within window
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### TESTING ###
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if self.test_flag:
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self.logged_success += 1
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except Exception as e:
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verbose_logger.exception(
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"litellm.router_strategy.lowest_latency.py::async_log_success_event(): Exception occured - {}".format(
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str(e)
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)
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)
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pass
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def get_available_deployments(
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self,
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model_group: str,
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healthy_deployments: list,
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messages: Optional[List[Dict[str, str]]] = None,
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input: Optional[Union[str, List]] = None,
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request_kwargs: Optional[Dict] = None,
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):
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"""
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Returns a deployment with the lowest latency
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"""
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# get list of potential deployments
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latency_key = f"{model_group}_map"
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_latency_per_deployment = {}
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request_count_dict = self.router_cache.get_cache(key=latency_key) or {}
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# -----------------------
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# Find lowest used model
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# ----------------------
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lowest_latency = float("inf")
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current_date = datetime.now().strftime("%Y-%m-%d")
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current_hour = datetime.now().strftime("%H")
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current_minute = datetime.now().strftime("%M")
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precise_minute = f"{current_date}-{current_hour}-{current_minute}"
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deployment = None
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if request_count_dict is None: # base case
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return
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all_deployments = request_count_dict
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for d in healthy_deployments:
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## if healthy deployment not yet used
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if d["model_info"]["id"] not in all_deployments:
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all_deployments[d["model_info"]["id"]] = {
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"latency": [0],
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precise_minute: {"tpm": 0, "rpm": 0},
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}
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try:
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input_tokens = token_counter(messages=messages, text=input)
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except Exception:
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input_tokens = 0
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# randomly sample from all_deployments, incase all deployments have latency=0.0
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_items = all_deployments.items()
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all_deployments = random.sample(list(_items), len(_items))
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all_deployments = dict(all_deployments)
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### GET AVAILABLE DEPLOYMENTS ### filter out any deployments > tpm/rpm limits
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potential_deployments = []
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for item, item_map in all_deployments.items():
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## get the item from model list
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_deployment = None
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for m in healthy_deployments:
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if item == m["model_info"]["id"]:
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_deployment = m
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if _deployment is None:
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continue # skip to next one
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_deployment_tpm = (
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_deployment.get("tpm", None)
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or _deployment.get("litellm_params", {}).get("tpm", None)
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or _deployment.get("model_info", {}).get("tpm", None)
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or float("inf")
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)
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_deployment_rpm = (
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_deployment.get("rpm", None)
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or _deployment.get("litellm_params", {}).get("rpm", None)
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or _deployment.get("model_info", {}).get("rpm", None)
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or float("inf")
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)
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item_latency = item_map.get("latency", [])
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item_ttft_latency = item_map.get("time_to_first_token", [])
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item_rpm = item_map.get(precise_minute, {}).get("rpm", 0)
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item_tpm = item_map.get(precise_minute, {}).get("tpm", 0)
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# get average latency or average ttft (depending on streaming/non-streaming)
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total: float = 0.0
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if (
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request_kwargs is not None
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and request_kwargs.get("stream", None) is not None
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and request_kwargs["stream"] is True
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and len(item_ttft_latency) > 0
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):
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for _call_latency in item_ttft_latency:
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if isinstance(_call_latency, float):
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total += _call_latency
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else:
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for _call_latency in item_latency:
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if isinstance(_call_latency, float):
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total += _call_latency
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item_latency = total / len(item_latency)
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# -------------- #
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# Debugging Logic
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# -------------- #
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# We use _latency_per_deployment to log to langfuse, slack - this is not used to make a decision on routing
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# this helps a user to debug why the router picked a specfic deployment #
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_deployment_api_base = _deployment.get("litellm_params", {}).get(
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"api_base", ""
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)
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if _deployment_api_base is not None:
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_latency_per_deployment[_deployment_api_base] = item_latency
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# -------------- #
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# End of Debugging Logic
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# -------------- #
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if (
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item_tpm + input_tokens > _deployment_tpm
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or item_rpm + 1 > _deployment_rpm
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): # if user passed in tpm / rpm in the model_list
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continue
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else:
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potential_deployments.append((_deployment, item_latency))
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if len(potential_deployments) == 0:
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return None
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# Sort potential deployments by latency
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sorted_deployments = sorted(potential_deployments, key=lambda x: x[1])
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# Find lowest latency deployment
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lowest_latency = sorted_deployments[0][1]
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# Find deployments within buffer of lowest latency
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buffer = self.routing_args.lowest_latency_buffer * lowest_latency
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valid_deployments = [
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x for x in sorted_deployments if x[1] <= lowest_latency + buffer
|
|
]
|
|
|
|
# Pick a random deployment from valid deployments
|
|
random_valid_deployment = random.choice(valid_deployments)
|
|
deployment = random_valid_deployment[0]
|
|
|
|
if request_kwargs is not None and "metadata" in request_kwargs:
|
|
request_kwargs["metadata"][
|
|
"_latency_per_deployment"
|
|
] = _latency_per_deployment
|
|
return deployment
|