diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index c51e76123e4..b5101898bb1 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -1161,6 +1161,43 @@ def _timed_out_earlier_records( return tuple(record for identity, record in by_identity.items() if identity != final_identity) +def _record_pricing( + model_call_details: Mapping[str, object], record: Mapping[str, object], base_model: str | None +) -> tuple[Mapping[str, object], str | None]: + """The ``(model_call_details, base_model)`` to price one earlier attempt with: the record's own + deployment model and ``base_model`` when it served a different model than the final attempt + (the provider is then inferred from that model), else the final attempt's.""" + record_model: Final = record.get("model") + if not isinstance(record_model, str) or record_model == model_call_details.get("model"): + return model_call_details, base_model + record_base_model: Final = record.get("base_model") + return ( + {**model_call_details, "model": record_model, "custom_llm_provider": None}, + record_base_model if isinstance(record_base_model, str) else None, + ) + + +def _billed_earlier_attempt( + model_call_details: Mapping[str, object], + record: Mapping[str, object], + index: int, + estimated_usage: Usage, + base_model: str | None, +) -> BilledFailedAttempt: + pricing_details, pricing_base_model = _record_pricing(model_call_details, record, base_model) + return BilledFailedAttempt( + attempted_retries=_attempt_number(record, index), + deployment_id=_record_deployment_id(record), + usage=estimated_usage, + response_cost=_estimated_input_cost( + pricing_details, + estimated_usage.prompt_tokens, + deployment_id=_record_deployment_id(record), + base_model=pricing_base_model, + ), + ) + + def _billed_earlier_attempts( model_call_details: Mapping[str, object], litellm_params: Mapping[str, object] | None, @@ -1174,23 +1211,14 @@ def _billed_earlier_attempts( request's own deployment and retry count (``attempted_retries`` restarts at 0 after a fallback hop, so the count alone cannot tell the groups apart). An earlier attempt that ended in a ``Timeout`` had the same prompt accepted by its deployment, so it is billed like the final - attempt, at that deployment's input rate (else the cost map's rate for ``base_model`` or the - model). Only the exception class survives on the record, so an earlier connect timeout is - billed too; any other failure class is not.""" + attempt, at that deployment's input rate (else the cost map's rate for the record's own + ``base_model`` or model, which a fallback hop can make a different model than the final one). + Only the exception class survives on the record, so an earlier connect timeout is billed too; + any other failure class is not.""" final_attempt: Final = _retry_metadata_bucket(litellm_params).get("attempted_retries") final_identity: Final = (deployment_id, final_attempt if isinstance(final_attempt, int) else None) return tuple( - BilledFailedAttempt( - attempted_retries=_attempt_number(record, index), - deployment_id=_record_deployment_id(record), - usage=estimated_usage, - response_cost=_estimated_input_cost( - model_call_details, - estimated_usage.prompt_tokens, - deployment_id=_record_deployment_id(record), - base_model=base_model, - ), - ) + _billed_earlier_attempt(model_call_details, record, index, estimated_usage, base_model) for index, record in enumerate(_timed_out_earlier_records(litellm_params, final_identity)) ) diff --git a/litellm/router.py b/litellm/router.py index 1c5a9176207..679f4eba1ea 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -9498,17 +9498,24 @@ class Router: When a retry or fallback happens, record which model group, deployment and attempt just failed and why, and count it toward the request-wide num_retries_per_request cap """ + from litellm.litellm_core_utils.get_litellm_params import get_base_model_from_litellm_call_metadata from litellm.types.router import RetryAttemptRecord _metadata_var: Final = "litellm_metadata" if "litellm_metadata" in kwargs else "metadata" - request_metadata: Final[Mapping[str, object]] = kwargs[_metadata_var] + request_metadata: Final = cast("Mapping[str, object]", kwargs[_metadata_var]) # cast-ok: untyped kwargs model_group: Final = kwargs.get("model") model_info: Final = request_metadata.get("model_info") deployment_id: Final = model_info.get("id") if isinstance(model_info, Mapping) else None + base_model: Final = get_base_model_from_litellm_call_metadata( + metadata=request_metadata + ) or self._deployment_params_base_model(deployment_id if isinstance(deployment_id, str) else None) + deployment_model: Final = request_metadata.get("deployment") attempted_retries: Final = request_metadata.get("attempted_retries") attempt_record: Final[RetryAttemptRecord] = { "model_group": model_group if isinstance(model_group, str) else None, "deployment_id": deployment_id if isinstance(deployment_id, str) else None, + "model": deployment_model if isinstance(deployment_model, str) else None, + "base_model": base_model if isinstance(base_model, str) else None, "exception_type": type(e).__name__, "exception_string": str(e), "attempted_retries": attempted_retries if type(attempted_retries) is int else None, @@ -9539,6 +9546,18 @@ class Router: kwargs[_metadata_var]["request_retry_count"] = request_retry_count # rebind-ok: same dict, read by the cap return kwargs + def _deployment_params_base_model(self, deployment_id: str | None) -> str | None: + """The ``base_model`` a deployment declares under ``litellm_params`` (the Azure named-deployment + shape), the same key the success path's ``get_base_model_from_metadata`` reads.""" + deployment: Final = self.get_deployment(model_id=deployment_id) if deployment_id is not None else None + if deployment is None: + return None + extra_params: Final = cast( # cast-ok: pydantic extras are untyped, base_model is isinstance-checked below + "Mapping[str, object]", deployment.litellm_params.model_extra or {} + ) + base_model: Final = extra_params.get("base_model") + return base_model if isinstance(base_model, str) else None + def _update_usage(self, deployment_id: str, parent_otel_span: Span | None) -> int: """ Update deployment rpm for that minute diff --git a/litellm/types/router.py b/litellm/types/router.py index 97b0d81d33b..cd1389aea9d 100644 --- a/litellm/types/router.py +++ b/litellm/types/router.py @@ -1184,6 +1184,8 @@ class RouterModelGroupAliasItem(TypedDict): class RetryAttemptRecord(TypedDict): model_group: ReadOnly[str | None] deployment_id: ReadOnly[str | None] + model: ReadOnly[str | None] + base_model: ReadOnly[str | None] exception_type: ReadOnly[str] exception_string: ReadOnly[str] attempted_retries: ReadOnly[int | None] diff --git a/tests/code_coverage_tests/router_code_coverage.py b/tests/code_coverage_tests/router_code_coverage.py index 7809a23e955..55435c51648 100644 --- a/tests/code_coverage_tests/router_code_coverage.py +++ b/tests/code_coverage_tests/router_code_coverage.py @@ -93,6 +93,7 @@ ignored_function_names = [ "_apply_updated_routing_strategy_args", # Tested via update_settings in test_lowest_latency.py (file lacks "router" in name) "_wait_for_scheduler_turn", # Tested through prioritized acompletion and atext_completion in test_router.py "arm_routing_read_prefetch", # Tested in tests/unit/caching/test_request_redis_batch_pre_call.py (file lacks "router" in name) + "_deployment_params_base_model", # Tested through log_retry in test_router_helper_utils.py "_configured_model_info", # Tested through get_configured_service_tiers in test_router.py "_routable_deployments", # Tested through get_configured_service_tiers and get_routable_upstream_model in test_router.py "_async_get_available_deployment", # Body of the `route {model}` phase wrapper, exercised through async_get_available_deployment in test_router.py diff --git a/tests/unit/proxy/test_proxy_utils_model_creation_and_error_logging.py b/tests/unit/proxy/test_proxy_utils_model_creation_and_error_logging.py index 960bbc9cba3..7b18cb3350c 100644 --- a/tests/unit/proxy/test_proxy_utils_model_creation_and_error_logging.py +++ b/tests/unit/proxy/test_proxy_utils_model_creation_and_error_logging.py @@ -2347,6 +2347,74 @@ def test_every_earlier_timed_out_attempt_is_billed_at_its_own_deployment_rate(mo assert all(a.usage is usage for a in attempts) +def test_an_earlier_attempt_on_another_model_is_priced_at_that_models_rate_not_the_final_models(monkeypatch): + """After a fallback hop the final attempt runs on another model group, so the records of the group + that timed out first name their own deployment model (and its ``base_model`` when the deployment + name is not in the cost map). Each is billed at that model's input rate, not at the final model's.""" + from litellm.proxy.utils import _billed_earlier_attempts + + for pricing_model, provider, input_rate in ( + ("lit145-final-model", "openai", 0.5), + ("lit145-first-model", "openai", 0.02), + ("azure/lit145-first-model", "azure", 0.02), + ): + monkeypatch.setitem( + litellm.model_cost, + pricing_model, + {"litellm_provider": provider, "mode": "chat", "input_cost_per_token": input_rate, "output_cost_per_token": 1.0}, + ) + usage = litellm.Usage(prompt_tokens=24, completion_tokens=0, total_tokens=24) + + attempts = _billed_earlier_attempts( + model_call_details={"model": "openai/lit145-final-model", "custom_llm_provider": "openai"}, + litellm_params={ + "metadata": { + "attempted_retries": 1, + "model_info": {"id": "dep-lit145-final"}, + "previous_models": ( + { + "deployment_id": "dep-lit145-first", + "model": "openai/lit145-first-model", + "base_model": None, + "exception_type": "Timeout", + "attempted_retries": 0, + }, + { + "deployment_id": "dep-lit145-first-azure", + "model": "azure/lit145-first-deployment", + "base_model": "azure/lit145-first-model", + "exception_type": "Timeout", + "attempted_retries": 1, + }, + { + "deployment_id": "dep-lit145-final", + "model": "openai/lit145-final-model", + "base_model": None, + "exception_type": "Timeout", + "attempted_retries": 0, + }, + { + "deployment_id": "dep-lit145-final", + "model": "openai/lit145-final-model", + "base_model": None, + "exception_type": "Timeout", + "attempted_retries": 1, + }, + ), + } + }, + estimated_usage=usage, + base_model=None, + deployment_id="dep-lit145-final", + ) + + assert [(a.attempted_retries, a.deployment_id, a.response_cost) for a in attempts] == [ + (0, "dep-lit145-first", pytest.approx(24 * 0.02)), + (1, "dep-lit145-first-azure", pytest.approx(24 * 0.02)), + (0, "dep-lit145-final", pytest.approx(24 * 0.5)), + ] + + def test_earlier_attempts_are_priced_from_the_prompt_estimate_not_the_final_streams_recovered_usage(): """A final attempt whose stream broke mid-flight lifts its recovered usage (prompt plus the chunks delivered); the earlier timed-out attempts never produced output, so they are priced from the diff --git a/tests/unit/test_router/test_router.py b/tests/unit/test_router/test_router.py index d645ab4566d..13ac55fa937 100644 --- a/tests/unit/test_router/test_router.py +++ b/tests/unit/test_router/test_router.py @@ -15195,7 +15195,7 @@ async def test_cyclic_fallback_graph_does_not_amplify_one_request(): _FLAT_ATTEMPT_RECORD_KEYS = frozenset( - {"model_group", "deployment_id", "exception_type", "exception_string", "attempted_retries"} + {"model_group", "deployment_id", "model", "base_model", "exception_type", "exception_string", "attempted_retries"} ) _BREADCRUMB_CREDENTIAL_CANARY = "Bearer sk-ant-oat01-RETRY-BREADCRUMB-CANARY-doNotShip" diff --git a/tests/unit/test_router/test_router_helper_utils.py b/tests/unit/test_router/test_router_helper_utils.py index e3061294bef..7088818aa01 100644 --- a/tests/unit/test_router/test_router_helper_utils.py +++ b/tests/unit/test_router/test_router_helper_utils.py @@ -837,7 +837,12 @@ def test_log_retry(model_list: list[DeploymentTypedDict], metadata_key: str) -> "model": "gpt-3.5-turbo", "api_key": "sk-must-not-be-recorded", "messages": [{"role": "user", "content": "hi"}], - metadata_key: {"model_info": {"id": "deployment-1"}, "attempted_retries": 2, "user_api_key": "sk-proxy"}, + metadata_key: { + "model_info": {"id": "deployment-1", "base_model": "azure/gpt-3.5-turbo"}, + "deployment": "azure/my-35-deployment", + "attempted_retries": 2, + "user_api_key": "sk-proxy", + }, }, e=rate_limit_error, ) @@ -845,6 +850,8 @@ def test_log_retry(model_list: list[DeploymentTypedDict], metadata_key: str) -> { "model_group": "gpt-3.5-turbo", "deployment_id": "deployment-1", + "model": "azure/my-35-deployment", + "base_model": "azure/gpt-3.5-turbo", "exception_type": "RateLimitError", "exception_string": "litellm.RateLimitError: slow down", "attempted_retries": 2, @@ -856,6 +863,38 @@ def test_log_retry(model_list: list[DeploymentTypedDict], metadata_key: str) -> assert router.log_retry(kwargs=planted_kwargs, e=rate_limit_error)[metadata_key]["request_retry_count"] == 1 +def test_log_retry_reads_base_model_from_the_deployments_litellm_params() -> None: + """An Azure named deployment declares ``base_model`` under ``litellm_params``, not ``model_info``, and + that is the model the failure row is priced at, so the retry record has to carry it too""" + router = Router( + model_list=[ + { + "model_name": "azure-group", + "litellm_params": { + "model": "azure/my-named-deployment", + "api_key": "sk-fake", + "api_base": "https://example.openai.azure.com", + "base_model": "azure/gpt-4o-mini", + }, + "model_info": {"id": "dep-azure-named"}, + } + ] + ) + new_kwargs = router.log_retry( + kwargs={ + "model": "azure-group", + "metadata": { + "model_info": {"id": "dep-azure-named"}, + "deployment": "azure/my-named-deployment", + "attempted_retries": 0, + }, + }, + e=litellm.Timeout(message="slow", llm_provider="azure", model="azure/my-named-deployment"), + ) + record = new_kwargs["metadata"]["previous_models"][0] + assert (record["model"], record["base_model"]) == ("azure/my-named-deployment", "azure/gpt-4o-mini") + + @pytest.mark.usefixtures("router_minute_pinned") def test_update_usage(model_list): """Test if the '_update_usage' function is working correctly"""