diff --git a/litellm/integrations/opentelemetry.py b/litellm/integrations/opentelemetry.py index 9456817a205..34b712d47e3 100644 --- a/litellm/integrations/opentelemetry.py +++ b/litellm/integrations/opentelemetry.py @@ -21,6 +21,7 @@ from litellm.integrations.opentelemetry_utils.gen_ai_semconv import ( OTELSemconvCategory, parse_semconv_opt_in, ) +from litellm.integrations.otel.mappers.utils import drop_none from litellm.integrations.otel.model.baggage import promoted_metadata from litellm.integrations.otel.model.db_endpoint import db_span_attributes from litellm.integrations.otel.model.metadata import flatten_metadata @@ -208,6 +209,20 @@ def _resolve_metric_attribute_filter( ) +def _provider_label(custom_llm_provider: object) -> str | None: + """The provider label for one call's metrics and events, or None when the + call carries no provider. + + Every attribute set drops None before export, so the label is simply absent + in that case: the OTLP encoder rejects a None attribute value outright, and a + placeholder would mint a permanent metric series that no operator can act + on. Mirrors the v2 integration's ``_provider_attributes``. + """ + if not isinstance(custom_llm_provider, str) or not custom_llm_provider: + return None + return custom_llm_provider + + def _normalize_team_metadata_keys(value: str | Iterable[object] | None) -> list[str]: """Coerce a team-metadata allowlist from a list or comma-separated string. @@ -1616,19 +1631,22 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): ) = _resolve_metric_attribute_filter(attributes) self._metric_attr_filter_resolved = True - def _filter_metric_attributes(self, attrs: dict[str, str]) -> dict[str, str]: + def _filter_metric_attributes(self, attrs: Mapping[str, str | None]) -> dict[str, str]: if not self._metric_attr_filter_resolved: self._ensure_metric_attribute_filter() + return {k: v for k, v in attrs.items() if v is not None and self._metric_attribute_allowed(k)} + + def _metric_attribute_allowed(self, key: str) -> bool: if self._metric_attr_include is not None: - return {k: v for k, v in attrs.items() if k in self._metric_attr_include} + return key in self._metric_attr_include if self._metric_attr_exclude is not None: - return {k: v for k, v in attrs.items() if k not in self._metric_attr_exclude} - return attrs + return key not in self._metric_attr_exclude + return True def _record_metrics(self, kwargs, response_obj, start_time, end_time): duration_s: Final = (end_time - start_time).total_seconds() params: Final = kwargs.get("litellm_params") or {} - provider: Final = params.get("custom_llm_provider", "Unknown") + provider: Final = _provider_label(params.get("custom_llm_provider")) common_attrs = { "gen_ai.operation.name": ( @@ -1872,7 +1890,7 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): otel_logger: Final = self._logger_provider.get_logger(LITELLM_LOGGER_NAME) parent_ctx: Final = span.get_span_context() - provider: Final = (kwargs.get("litellm_params") or {}).get("custom_llm_provider", "Unknown") + provider: Final = _provider_label((kwargs.get("litellm_params") or {}).get("custom_llm_provider")) if self._gen_ai_semconv_latest_experimental: self._emit_inference_details_event( @@ -1909,7 +1927,7 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): severity_number=SeverityNumber.INFO, severity_text="INFO", body=body, - attributes=attrs, + attributes=drop_none(attrs), ) otel_logger.emit(log_record) @@ -1941,7 +1959,7 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): severity_number=SeverityNumber.INFO, severity_text="INFO", body=body, - attributes=attrs, + attributes=drop_none(attrs), ) otel_logger.emit(log_record) diff --git a/litellm/integrations/opentelemetry_utils/gen_ai_semconv.py b/litellm/integrations/opentelemetry_utils/gen_ai_semconv.py index b5eedc42fe9..81d9a947da7 100644 --- a/litellm/integrations/opentelemetry_utils/gen_ai_semconv.py +++ b/litellm/integrations/opentelemetry_utils/gen_ai_semconv.py @@ -33,6 +33,7 @@ from datetime import datetime from enum import Enum from typing import TYPE_CHECKING, Any, Final +from litellm.integrations.otel.mappers.utils import drop_none from litellm.litellm_core_utils.safe_json_dumps import safe_dumps if TYPE_CHECKING: @@ -195,13 +196,16 @@ class OTELGenAISemconvMixin: if value: self.safe_set_attribute(span=span, key=semconv_key, value=value) - def _build_inference_details_attrs(self, kwargs: dict, response_obj: dict, provider: str) -> dict[str, str]: + def _build_inference_details_attrs( + self, kwargs: dict, response_obj: dict, provider: str | None + ) -> dict[str, str | None]: """Build the attribute payload for the inference-details event. - Always includes provider/operation; input/output messages are added + Always includes operation and provider (None when the call carries none, + dropped before the event is emitted); input/output messages are added only when content capture is enabled and non-empty. Mixin-internal. """ - attrs: Final[dict[str, str]] = { + attrs: Final[dict[str, str | None]] = { "event_name": _INFERENCE_DETAILS_EVENT_NAME, "gen_ai.provider.name": provider, "gen_ai.operation.name": self._gen_ai_operation_name(kwargs), @@ -221,7 +225,7 @@ class OTELGenAISemconvMixin: self, kwargs: dict, response_obj: dict, - provider: str, + provider: str | None, otel_logger, parent_ctx, ) -> None: @@ -239,6 +243,6 @@ class OTELGenAISemconvMixin: severity_number=SeverityNumber.INFO, severity_text="INFO", body=None, - attributes=self._build_inference_details_attrs(kwargs, response_obj, provider), + attributes=drop_none(self._build_inference_details_attrs(kwargs, response_obj, provider)), ) otel_logger.emit(log_record) diff --git a/tests/test_litellm/integrations/test_opentelemetry.py b/tests/test_litellm/integrations/test_opentelemetry.py index 7812590b3e7..7d1faf93116 100644 --- a/tests/test_litellm/integrations/test_opentelemetry.py +++ b/tests/test_litellm/integrations/test_opentelemetry.py @@ -15,10 +15,11 @@ from unittest.mock import MagicMock, patch # Adds the grandparent directory to sys.path to allow importing project modules from opentelemetry import trace +from opentelemetry.sdk._logs import LogData from opentelemetry.sdk._logs import LoggerProvider as OTLoggerProvider from opentelemetry.sdk._logs.export import InMemoryLogExporter, SimpleLogRecordProcessor from opentelemetry.sdk.metrics import MeterProvider -from opentelemetry.sdk.metrics.export import InMemoryMetricReader +from opentelemetry.sdk.metrics.export import InMemoryMetricReader, MetricsData from opentelemetry.sdk.trace import TracerProvider from opentelemetry.sdk.trace.export import SimpleSpanProcessor from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter @@ -5921,13 +5922,11 @@ class TestOpenTelemetryMetricAttributeFiltering(unittest.TestCase): } ) - def test_no_filter_returns_attrs_object_unchanged(self): - """The no-config path is a hot-path no-op: it returns the same dict - object, so default emission pays zero copy cost. Locking identity makes - a future refactor that always copies/filters trip here.""" + def test_no_filter_keeps_every_attribute(self): + """The no-config path drops nothing: every attribute the caller set reaches the meter.""" otel = OpenTelemetry(config=OpenTelemetryConfig(exporter="console")) attrs = {"gen_ai.request.model": "m", "hidden_params": "{}"} - self.assertIs(otel._filter_metric_attributes(attrs), attrs) + self.assertEqual(otel._filter_metric_attributes(attrs), attrs) def test_token_type_discriminator_rejected_from_either_list(self): """gen_ai.token.type is a structural discriminator stamped onto the @@ -6068,6 +6067,118 @@ class TestOTELServiceTierAttributes(unittest.TestCase): self.assertEqual(attributes[self.RESPONSE_KEY], "tier-added-by-provider-later") +class TestOpenTelemetryProviderlessCallAttributes(unittest.TestCase): + """Regression for the OTLP exporter rejecting a None gen_ai.system or gen_ai.request.model + attribute on every export cycle.""" + + HERE = os.path.dirname(__file__) + POLL_INTERVAL = 0.05 + POLL_TIMEOUT = 2.0 + + def _providerless_kwargs(self) -> tuple[dict[str, object], dict[str, object]]: + with open(os.path.join(self.HERE, "open_telemetry", "data", "captured_kwargs.json")) as f: + kwargs = json.load(f) + with open(os.path.join(self.HERE, "open_telemetry", "data", "captured_response.json")) as f: + response_obj = json.load(f) + kwargs["litellm_params"]["custom_llm_provider"] = None + return kwargs, response_obj + + def _modelless_kwargs(self) -> tuple[dict[str, object], dict[str, object]]: + kwargs, response_obj = self._providerless_kwargs() + kwargs["model"] = None + return kwargs, response_obj + + def _recorded_metrics(self, kwargs: dict[str, object], response_obj: dict[str, object]) -> MetricsData | None: + metric_reader = InMemoryMetricReader() + meter_provider = MeterProvider(metric_readers=[metric_reader]) + tracer_provider = TracerProvider() + tracer_provider.add_span_processor(SimpleSpanProcessor(InMemorySpanExporter())) + otel = OpenTelemetry( + config=OpenTelemetryConfig(exporter="console", enable_metrics=True), + tracer_provider=tracer_provider, + meter_provider=meter_provider, + ) + otel.tracer = tracer_provider.get_tracer(__name__) + + start = datetime.utcnow() + otel._handle_success(kwargs, response_obj, start, start + timedelta(seconds=1)) + + deadline = time.time() + self.POLL_TIMEOUT + while time.time() < deadline: + data = metric_reader.get_metrics_data() + if data and getattr(data, "resource_metrics", None): + return data + time.sleep(self.POLL_INTERVAL) + return None + + def _emitted_log_records(self, semconv_opt_in: str) -> tuple[LogData, ...]: + log_exporter = InMemoryLogExporter() + logger_provider = OTLoggerProvider() + logger_provider.add_log_record_processor(SimpleLogRecordProcessor(log_exporter)) + with patch.dict(os.environ, {"OTEL_SEMCONV_STABILITY_OPT_IN": semconv_opt_in}): + handler = OpenTelemetry( + config=OpenTelemetryConfig(exporter="console", enable_events=True), + logger_provider=logger_provider, + ) + handler.message_logging = True + + kwargs, response_obj = self._providerless_kwargs() + span = handler.tracer.start_span("test") + with self.assertNoLogs("opentelemetry.attributes", level="WARNING"): + handler._emit_semantic_logs(kwargs, response_obj, span) + span.end() + handler._logger_provider.force_flush(2000) + return log_exporter.get_finished_logs() + + def _assert_every_attribute_encodes(self, attrs: dict[str, object]) -> None: + from opentelemetry.exporter.otlp.proto.common._internal import _encode_attributes + + self.assertEqual(len(_encode_attributes(attrs) or []), len(attrs)) + + def _recorded_data_points(self, kwargs: dict[str, object], response_obj: dict[str, object]) -> list[object]: + data = self._recorded_metrics(kwargs, response_obj) + self.assertIsNotNone(data, "no metrics were recorded") + data_points = [ + dp + for rm in data.resource_metrics + for sm in rm.scope_metrics + for m in sm.metrics + for dp in m.data.data_points + ] + self.assertTrue(data_points, "no metric data points were recorded") + return data_points + + def test_metrics_are_encodable_and_carry_no_provider_label(self): + kwargs, response_obj = self._providerless_kwargs() + for dp in self._recorded_data_points(kwargs, response_obj): + self.assertNotIn("gen_ai.system", dp.attributes) + self.assertEqual(dp.attributes["gen_ai.request.model"], kwargs["model"]) + self._assert_every_attribute_encodes(dict(dp.attributes)) + + def test_metrics_are_encodable_and_carry_no_model_label_when_the_call_has_none(self): + for dp in self._recorded_data_points(*self._modelless_kwargs()): + self.assertNotIn("gen_ai.request.model", dp.attributes) + self._assert_every_attribute_encodes(dict(dp.attributes)) + + def test_legacy_content_events_are_encodable_and_carry_no_provider_label(self): + logs = self._emitted_log_records("") + self.assertTrue(logs, "no content events were emitted") + for log in logs: + attrs = dict(log.log_record.attributes or {}) + self.assertNotIn("gen_ai.system", attrs) + self.assertNotIn(None, attrs.values()) + self._assert_every_attribute_encodes(attrs) + + def test_inference_details_event_is_encodable_and_carries_no_provider_label(self): + logs = self._emitted_log_records("gen_ai_latest_experimental") + self.assertEqual(len(logs), 1) + attrs = dict(logs[0].log_record.attributes or {}) + self.assertEqual(attrs["event_name"], "gen_ai.client.inference.operation.details") + self.assertNotIn("gen_ai.provider.name", attrs) + self.assertNotIn(None, attrs.values()) + self._assert_every_attribute_encodes(attrs) + + class TestDynamicTracerProviderCache(unittest.TestCase): """Every credential-scoped TracerProvider that owns its exporter also owns a BatchSpanProcessor worker thread that only stops on shutdown, so the cache holding them