forked from phoenix/litellm-mirror
342 lines
12 KiB
Python
342 lines
12 KiB
Python
#### What this does ####
|
|
# picks based on response time (for streaming, this is time to first token)
|
|
from pydantic import BaseModel, Extra, Field, root_validator
|
|
import dotenv, os, requests, random
|
|
from typing import Optional, Union, List, Dict
|
|
from datetime import datetime, timedelta
|
|
import random
|
|
|
|
dotenv.load_dotenv() # Loading env variables using dotenv
|
|
import traceback
|
|
from litellm.caching import DualCache
|
|
from litellm.integrations.custom_logger import CustomLogger
|
|
from litellm._logging import verbose_router_logger
|
|
from litellm import ModelResponse
|
|
from litellm import token_counter
|
|
import litellm
|
|
|
|
|
|
class LiteLLMBase(BaseModel):
|
|
"""
|
|
Implements default functions, all pydantic objects should have.
|
|
"""
|
|
|
|
def json(self, **kwargs):
|
|
try:
|
|
return self.model_dump() # noqa
|
|
except:
|
|
# if using pydantic v1
|
|
return self.dict()
|
|
|
|
|
|
class LowestCostLoggingHandler(CustomLogger):
|
|
test_flag: bool = False
|
|
logged_success: int = 0
|
|
logged_failure: int = 0
|
|
|
|
def __init__(
|
|
self, router_cache: DualCache, model_list: list, routing_args: dict = {}
|
|
):
|
|
self.router_cache = router_cache
|
|
self.model_list = model_list
|
|
|
|
def log_success_event(self, kwargs, response_obj, start_time, end_time):
|
|
try:
|
|
"""
|
|
Update usage on success
|
|
"""
|
|
if kwargs["litellm_params"].get("metadata") is None:
|
|
pass
|
|
else:
|
|
model_group = kwargs["litellm_params"]["metadata"].get(
|
|
"model_group", None
|
|
)
|
|
|
|
id = kwargs["litellm_params"].get("model_info", {}).get("id", None)
|
|
if model_group is None or id is None:
|
|
return
|
|
elif isinstance(id, int):
|
|
id = str(id)
|
|
|
|
# ------------
|
|
# Setup values
|
|
# ------------
|
|
"""
|
|
{
|
|
{model_group}_map: {
|
|
id: {
|
|
f"{date:hour:minute}" : {"tpm": 34, "rpm": 3}
|
|
}
|
|
}
|
|
}
|
|
"""
|
|
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}"
|
|
cost_key = f"{model_group}_map"
|
|
|
|
response_ms: timedelta = end_time - start_time
|
|
|
|
final_value = response_ms
|
|
total_tokens = 0
|
|
|
|
if isinstance(response_obj, ModelResponse):
|
|
completion_tokens = response_obj.usage.completion_tokens
|
|
total_tokens = response_obj.usage.total_tokens
|
|
final_value = float(response_ms.total_seconds() / completion_tokens)
|
|
|
|
# ------------
|
|
# Update usage
|
|
# ------------
|
|
|
|
request_count_dict = self.router_cache.get_cache(key=cost_key) or {}
|
|
|
|
if id not in request_count_dict:
|
|
request_count_dict[id] = {}
|
|
|
|
if precise_minute not in request_count_dict[id]:
|
|
request_count_dict[id][precise_minute] = {}
|
|
|
|
if precise_minute not in request_count_dict[id]:
|
|
request_count_dict[id][precise_minute] = {}
|
|
|
|
## TPM
|
|
request_count_dict[id][precise_minute]["tpm"] = (
|
|
request_count_dict[id][precise_minute].get("tpm", 0) + total_tokens
|
|
)
|
|
|
|
## RPM
|
|
request_count_dict[id][precise_minute]["rpm"] = (
|
|
request_count_dict[id][precise_minute].get("rpm", 0) + 1
|
|
)
|
|
|
|
self.router_cache.set_cache(key=cost_key, value=request_count_dict)
|
|
|
|
### TESTING ###
|
|
if self.test_flag:
|
|
self.logged_success += 1
|
|
except Exception as e:
|
|
traceback.print_exc()
|
|
pass
|
|
|
|
async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
|
|
try:
|
|
"""
|
|
Update cost usage on success
|
|
"""
|
|
if kwargs["litellm_params"].get("metadata") is None:
|
|
pass
|
|
else:
|
|
model_group = kwargs["litellm_params"]["metadata"].get(
|
|
"model_group", None
|
|
)
|
|
|
|
id = kwargs["litellm_params"].get("model_info", {}).get("id", None)
|
|
if model_group is None or id is None:
|
|
return
|
|
elif isinstance(id, int):
|
|
id = str(id)
|
|
|
|
# ------------
|
|
# Setup values
|
|
# ------------
|
|
"""
|
|
{
|
|
{model_group}_map: {
|
|
id: {
|
|
"cost": [..]
|
|
f"{date:hour:minute}" : {"tpm": 34, "rpm": 3}
|
|
}
|
|
}
|
|
}
|
|
"""
|
|
cost_key = f"{model_group}_map"
|
|
|
|
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}"
|
|
|
|
response_ms: timedelta = end_time - start_time
|
|
|
|
final_value = response_ms
|
|
total_tokens = 0
|
|
|
|
if isinstance(response_obj, ModelResponse):
|
|
completion_tokens = response_obj.usage.completion_tokens
|
|
total_tokens = response_obj.usage.total_tokens
|
|
final_value = float(response_ms.total_seconds() / completion_tokens)
|
|
|
|
# ------------
|
|
# Update usage
|
|
# ------------
|
|
|
|
request_count_dict = self.router_cache.get_cache(key=cost_key) or {}
|
|
|
|
if id not in request_count_dict:
|
|
request_count_dict[id] = {}
|
|
if precise_minute not in request_count_dict[id]:
|
|
request_count_dict[id][precise_minute] = {}
|
|
|
|
## TPM
|
|
request_count_dict[id][precise_minute]["tpm"] = (
|
|
request_count_dict[id][precise_minute].get("tpm", 0) + total_tokens
|
|
)
|
|
|
|
## RPM
|
|
request_count_dict[id][precise_minute]["rpm"] = (
|
|
request_count_dict[id][precise_minute].get("rpm", 0) + 1
|
|
)
|
|
|
|
self.router_cache.set_cache(
|
|
key=cost_key, value=request_count_dict
|
|
) # reset map within window
|
|
|
|
### TESTING ###
|
|
if self.test_flag:
|
|
self.logged_success += 1
|
|
except Exception as e:
|
|
traceback.print_exc()
|
|
pass
|
|
|
|
def get_available_deployments(
|
|
self,
|
|
model_group: str,
|
|
healthy_deployments: list,
|
|
messages: Optional[List[Dict[str, str]]] = None,
|
|
input: Optional[Union[str, List]] = None,
|
|
request_kwargs: Optional[Dict] = None,
|
|
):
|
|
"""
|
|
Returns a deployment with the lowest cost
|
|
"""
|
|
cost_key = f"{model_group}_map"
|
|
|
|
request_count_dict = self.router_cache.get_cache(key=cost_key) or {}
|
|
|
|
# -----------------------
|
|
# Find lowest used model
|
|
# ----------------------
|
|
lowest_cost = float("inf")
|
|
|
|
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}"
|
|
|
|
deployment = None
|
|
|
|
if request_count_dict is None: # base case
|
|
return
|
|
|
|
all_deployments = request_count_dict
|
|
for d in healthy_deployments:
|
|
## if healthy deployment not yet used
|
|
if d["model_info"]["id"] not in all_deployments:
|
|
all_deployments[d["model_info"]["id"]] = {
|
|
precise_minute: {"tpm": 0, "rpm": 0},
|
|
}
|
|
|
|
try:
|
|
input_tokens = token_counter(messages=messages, text=input)
|
|
except:
|
|
input_tokens = 0
|
|
|
|
# randomly sample from all_deployments, incase all deployments have latency=0.0
|
|
_items = all_deployments.items()
|
|
|
|
### GET AVAILABLE DEPLOYMENTS ### filter out any deployments > tpm/rpm limits
|
|
potential_deployments = []
|
|
_cost_per_deployment = {}
|
|
for item, item_map in all_deployments.items():
|
|
## get the item from model list
|
|
_deployment = None
|
|
for m in healthy_deployments:
|
|
if item == m["model_info"]["id"]:
|
|
_deployment = m
|
|
|
|
if _deployment is None:
|
|
continue # skip to next one
|
|
|
|
_deployment_tpm = (
|
|
_deployment.get("tpm", None)
|
|
or _deployment.get("litellm_params", {}).get("tpm", None)
|
|
or _deployment.get("model_info", {}).get("tpm", None)
|
|
or float("inf")
|
|
)
|
|
|
|
_deployment_rpm = (
|
|
_deployment.get("rpm", None)
|
|
or _deployment.get("litellm_params", {}).get("rpm", None)
|
|
or _deployment.get("model_info", {}).get("rpm", None)
|
|
or float("inf")
|
|
)
|
|
item_litellm_model_name = _deployment.get("litellm_params", {}).get("model")
|
|
item_litellm_model_cost_map = litellm.model_cost.get(
|
|
item_litellm_model_name, {}
|
|
)
|
|
|
|
# check if user provided input_cost_per_token and output_cost_per_token in litellm_params
|
|
item_input_cost = None
|
|
item_output_cost = None
|
|
if _deployment.get("litellm_params", {}).get("input_cost_per_token", None):
|
|
item_input_cost = _deployment.get("litellm_params", {}).get(
|
|
"input_cost_per_token"
|
|
)
|
|
|
|
if _deployment.get("litellm_params", {}).get("output_cost_per_token", None):
|
|
item_output_cost = _deployment.get("litellm_params", {}).get(
|
|
"output_cost_per_token"
|
|
)
|
|
|
|
if item_input_cost is None:
|
|
item_input_cost = item_litellm_model_cost_map.get(
|
|
"input_cost_per_token", 5.0
|
|
)
|
|
|
|
if item_output_cost is None:
|
|
item_output_cost = item_litellm_model_cost_map.get(
|
|
"output_cost_per_token", 5.0
|
|
)
|
|
|
|
# if litellm["model"] is not in model_cost map -> use item_cost = $10
|
|
|
|
item_cost = item_input_cost + item_output_cost
|
|
|
|
item_rpm = item_map.get(precise_minute, {}).get("rpm", 0)
|
|
item_tpm = item_map.get(precise_minute, {}).get("tpm", 0)
|
|
|
|
verbose_router_logger.debug(
|
|
f"item_cost: {item_cost}, item_tpm: {item_tpm}, item_rpm: {item_rpm}, model_id: {_deployment.get('model_info', {}).get('id')}"
|
|
)
|
|
|
|
# -------------- #
|
|
# Debugging Logic
|
|
# -------------- #
|
|
# We use _cost_per_deployment to log to langfuse, slack - this is not used to make a decision on routing
|
|
# this helps a user to debug why the router picked a specfic deployment #
|
|
_deployment_api_base = _deployment.get("litellm_params", {}).get(
|
|
"api_base", ""
|
|
)
|
|
if _deployment_api_base is not None:
|
|
_cost_per_deployment[_deployment_api_base] = item_cost
|
|
# -------------- #
|
|
# End of Debugging Logic
|
|
# -------------- #
|
|
|
|
if (
|
|
item_tpm + input_tokens > _deployment_tpm
|
|
or item_rpm + 1 > _deployment_rpm
|
|
): # if user passed in tpm / rpm in the model_list
|
|
continue
|
|
else:
|
|
potential_deployments.append((_deployment, item_cost))
|
|
|
|
if len(potential_deployments) == 0:
|
|
return None
|
|
|
|
potential_deployments = sorted(potential_deployments, key=lambda x: x[1])
|
|
|
|
selected_deployment = potential_deployments[0][0]
|
|
return selected_deployment
|