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