Merge pull request #36815 from BerriAI/litellm_otel_gen_ai_system_none

fix(otel): drop None metric and event attributes before OTLP export

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 key not in self._metric_attr_exclude
-        return attrs
+        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)
 

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)

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):
+    def test_no_filter_keeps_every_attribute(self):
-        """The no-config path is a hot-path no-op: it returns the same dict
+        """The no-config path drops nothing: every attribute the caller set reaches the meter."""
-        object, so default emission pays zero copy cost. Locking identity makes
-        a future refactor that always copies/filters trip here."""
         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