litellm-mirror/litellm/router_utils/handle_error.py
Krish Dholakia 1e403a8447
Litellm dev 10 29 2024 (#6502)
* fix(core_helpers.py): return None, instead of raising kwargs is None error

Closes https://github.com/BerriAI/litellm/issues/6500

* docs(cost_tracking.md): cleanup doc

* fix(vertex_and_google_ai_studio.py): handle function call with no params passed in

Closes https://github.com/BerriAI/litellm/issues/6495

* test(test_router_timeout.py): add test for router timeout + retry logic

* test: update test to use module level values

* (fix) Prometheus - Log Postgres DB latency, status on prometheus  (#6484)

* fix logging DB fails on prometheus

* unit testing log to otel wrapper

* unit testing for service logger + prometheus

* use LATENCY buckets for service logging

* fix service logging

* docs clarify vertex vs gemini

* (router_strategy/) ensure all async functions use async cache methods (#6489)

* fix router strat

* use async set / get cache in router_strategy

* add coverage for router strategy

* fix imports

* fix batch_get_cache

* use async methods for least busy

* fix least busy use async methods

* fix test_dual_cache_increment

* test async_get_available_deployment when routing_strategy="least-busy"

* (fix) proxy - fix when `STORE_MODEL_IN_DB` should be set (#6492)

* set store_model_in_db at the top

* correctly use store_model_in_db global

* (fix) `PrometheusServicesLogger` `_get_metric` should return metric in Registry  (#6486)

* fix logging DB fails on prometheus

* unit testing log to otel wrapper

* unit testing for service logger + prometheus

* use LATENCY buckets for service logging

* fix service logging

* fix _get_metric in prom services logger

* add clear doc string

* unit testing for prom service logger

* bump: version 1.51.0 → 1.51.1

* Add `azure/gpt-4o-mini-2024-07-18` to model_prices_and_context_window.json (#6477)

* Update utils.py (#6468)

Fixed missing keys

* (perf) Litellm redis router fix - ~100ms improvement (#6483)

* docs(exception_mapping.md): add missing exception types

Fixes https://github.com/Aider-AI/aider/issues/2120#issuecomment-2438971183

* fix(main.py): register custom model pricing with specific key

Ensure custom model pricing is registered to the specific model+provider key combination

* test: make testing more robust for custom pricing

* fix(redis_cache.py): instrument otel logging for sync redis calls

ensures complete coverage for all redis cache calls

* refactor: pass parent_otel_span for redis caching calls in router

allows for more observability into what calls are causing latency issues

* test: update tests with new params

* refactor: ensure e2e otel tracing for router

* refactor(router.py): add more otel tracing acrosss router

catch all latency issues for router requests

* fix: fix linting error

* fix(router.py): fix linting error

* fix: fix test

* test: fix tests

* fix(dual_cache.py): pass ttl to redis cache

* fix: fix param

* perf(cooldown_cache.py): improve cooldown cache, to store cache results in memory for 5s, prevents redis call from being made on each request

reduces 100ms latency per call with caching enabled on router

* fix: fix test

* fix(cooldown_cache.py): handle if a result is None

* fix(cooldown_cache.py): add debug statements

* refactor(dual_cache.py): move to using an in-memory check for batch get cache, to prevent redis from being hit for every call

* fix(cooldown_cache.py): fix linting erropr

* refactor(prometheus.py): move to using standard logging payload for reading the remaining request / tokens

Ensures prometheus token tracking works for anthropic as well

* fix: fix linting error

* fix(redis_cache.py): make sure ttl is always int (handle float values)

Fixes issue where redis_client.ex was not working correctly due to float ttl

* fix: fix linting error

* test: update test

* fix: fix linting error

---------

Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Xingyao Wang <xingyao@all-hands.dev>
Co-authored-by: vibhanshu-ob <115142120+vibhanshu-ob@users.noreply.github.com>
2024-10-29 22:04:16 -07:00

91 lines
2.9 KiB
Python

import asyncio
import traceback
from typing import TYPE_CHECKING, Any, Optional
from litellm._logging import verbose_router_logger
from litellm.router_utils.cooldown_handlers import _async_get_cooldown_deployments
from litellm.types.integrations.slack_alerting import AlertType
from litellm.types.router import RouterRateLimitError
if TYPE_CHECKING:
from opentelemetry.trace import Span as _Span
from litellm.router import Router as _Router
LitellmRouter = _Router
Span = _Span
else:
LitellmRouter = Any
Span = Any
async def send_llm_exception_alert(
litellm_router_instance: LitellmRouter,
request_kwargs: dict,
error_traceback_str: str,
original_exception,
):
"""
Only runs if router.slack_alerting_logger is set
Sends a Slack / MS Teams alert for the LLM API call failure. Only if router.slack_alerting_logger is set.
Parameters:
litellm_router_instance (_Router): The LitellmRouter instance.
original_exception (Any): The original exception that occurred.
Returns:
None
"""
if litellm_router_instance is None:
return
if not hasattr(litellm_router_instance, "slack_alerting_logger"):
return
if litellm_router_instance.slack_alerting_logger is None:
return
if "proxy_server_request" in request_kwargs:
# Do not send any alert if it's a request from litellm proxy server request
# the proxy is already instrumented to send LLM API call failures
return
litellm_debug_info = getattr(original_exception, "litellm_debug_info", None)
exception_str = str(original_exception)
if litellm_debug_info is not None:
exception_str += litellm_debug_info
exception_str += f"\n\n{error_traceback_str[:2000]}"
await litellm_router_instance.slack_alerting_logger.send_alert(
message=f"LLM API call failed: `{exception_str}`",
level="High",
alert_type=AlertType.llm_exceptions,
alerting_metadata={},
)
async def async_raise_no_deployment_exception(
litellm_router_instance: LitellmRouter, model: str, parent_otel_span: Optional[Span]
):
"""
Raises a RouterRateLimitError if no deployment is found for the given model.
"""
verbose_router_logger.info(
f"get_available_deployment for model: {model}, No deployment available"
)
model_ids = litellm_router_instance.get_model_ids(model_name=model)
_cooldown_time = litellm_router_instance.cooldown_cache.get_min_cooldown(
model_ids=model_ids, parent_otel_span=parent_otel_span
)
_cooldown_list = await _async_get_cooldown_deployments(
litellm_router_instance=litellm_router_instance,
parent_otel_span=parent_otel_span,
)
return RouterRateLimitError(
model=model,
cooldown_time=_cooldown_time,
enable_pre_call_checks=litellm_router_instance.enable_pre_call_checks,
cooldown_list=_cooldown_list,
)