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feat(otel): stamp gen_ai.response.time_to_first_chunk on streaming LLM spans (#32236)
(cherry picked from commit 3116ed211b)
This commit is contained in:
parent
b5dee35fb3
commit
2d35ea5d07
7 changed files with 72 additions and 9 deletions
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@ -368,7 +368,11 @@ class OpenTelemetryV2(CustomLogger):
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# it (named provisionally) so it isn't leaked as an open span.
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carrier.span.end(end_time=to_ns(end_time))
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return None
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data = LLMCallSpanData.from_standard_logging_payload(payload, capture_content=self.config.capture_span_content)
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data = LLMCallSpanData.from_standard_logging_payload(
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payload,
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capture_content=self.config.capture_span_content,
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time_to_first_chunk_seconds=call.time_to_first_chunk_seconds,
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)
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end_time_ns = to_ns(end_time)
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if carrier.span is not None:
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# Born at the boundary: stamp attributes from the typed payload, set
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@ -55,6 +55,7 @@ class GenAIMapper:
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GenAI.RESPONSE_MODEL: lambda d: d.response_model,
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GenAI.RESPONSE_ID: lambda d: d.response_id,
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GenAI.RESPONSE_FINISH_REASONS: lambda d: list(d.finish_reasons) if d.finish_reasons else None,
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GenAI.RESPONSE_TIME_TO_FIRST_CHUNK: lambda d: d.time_to_first_chunk_seconds,
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GenAI.USAGE_INPUT_TOKENS: lambda d: d.usage.input_tokens,
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GenAI.USAGE_OUTPUT_TOKENS: lambda d: d.usage.output_tokens,
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Error.TYPE: lambda d: d.error.error_type if d.error else None,
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@ -41,7 +41,7 @@ from typing import TYPE_CHECKING, Any, Mapping, cast
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from litellm.constants import LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL
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from litellm.integrations.otel.model.semconv import resolve_operation
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from litellm.integrations.otel.model.utils import as_str
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from litellm.integrations.otel.model.utils import as_str, to_seconds
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if TYPE_CHECKING:
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from litellm.types.utils import StandardLoggingPayload
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@ -201,6 +201,7 @@ class LLMCallEvent:
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# span is renamed from the typed payload at close (``finish_span``); this only
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# needs to be reasonable for a span that never gets closed (a leak).
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provisional_span_name: str
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time_to_first_chunk_seconds: float | None
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@classmethod
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def from_dict(cls, kwargs: Mapping[str, Any]) -> "LLMCallEvent":
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@ -214,9 +215,25 @@ class LLMCallEvent:
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dynamic_params=kwargs.get("standard_callback_dynamic_params"),
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is_no_upstream_call=bool(kwargs.get(LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL)),
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provisional_span_name=f"{operation.value} {model}".strip(),
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time_to_first_chunk_seconds=time_to_first_chunk_seconds(kwargs),
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)
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def time_to_first_chunk_seconds(kwargs: Mapping[str, Any]) -> float | None:
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"""Seconds from the upstream request being issued (``api_call_start_time``)
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to the first streamed chunk (``completion_start_time``); ``None`` for
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non-streaming calls, where ``completion_start_time`` is backfilled with the
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end time and would not measure first-chunk latency."""
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optional_params = cast(Mapping[str, Any], kwargs.get("optional_params") or {})
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if not optional_params.get("stream"):
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return None
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api_call_start = to_seconds(kwargs.get("api_call_start_time"))
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completion_start = to_seconds(kwargs.get("completion_start_time"))
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if api_call_start is None or completion_start is None:
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return None
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return completion_start - api_call_start
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def _call_id(payload: "StandardLoggingPayload | None", kwargs: Mapping[str, Any]) -> str | None:
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"""The call id from the payload (when closed) or the bare kwargs (at pre_call)."""
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if payload is not None:
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@ -305,10 +305,14 @@ class LLMCallSpanData:
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messages_in: tuple[Mapping[str, object], ...] = ()
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choices_out: tuple[Mapping[str, object], ...] = ()
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system_fingerprint: str | None = None
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time_to_first_chunk_seconds: float | None = None
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@classmethod
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def from_standard_logging_payload(
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cls, payload: "StandardLoggingPayload", capture_content: bool = False
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cls,
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payload: "StandardLoggingPayload",
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capture_content: bool = False,
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time_to_first_chunk_seconds: float | None = None,
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) -> "LLMCallSpanData":
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params = cast(Mapping[str, object], payload.get("model_parameters") or {})
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# The single parse of the request's metadata — the request-vs-provider
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@ -349,6 +353,7 @@ class LLMCallSpanData:
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messages_in=_dicts(payload.get("messages")) if capture_content else (),
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choices_out=choices_out if capture_content else (),
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system_fingerprint=as_str(response.get("system_fingerprint")),
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time_to_first_chunk_seconds=time_to_first_chunk_seconds,
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)
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@ -69,6 +69,7 @@ class GenAI:
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RESPONSE_ID: Final = "gen_ai.response.id"
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RESPONSE_MODEL: Final = "gen_ai.response.model"
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RESPONSE_FINISH_REASONS: Final = "gen_ai.response.finish_reasons"
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RESPONSE_TIME_TO_FIRST_CHUNK: Final = "gen_ai.response.time_to_first_chunk"
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# usage
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USAGE_INPUT_TOKENS: Final = "gen_ai.usage.input_tokens"
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USAGE_OUTPUT_TOKENS: Final = "gen_ai.usage.output_tokens"
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@ -21,6 +21,7 @@ from litellm.integrations.opentelemetry import (
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_build_metric_attribute_filter,
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_resolve_metric_attribute_filter,
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)
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from litellm.integrations.otel.model.metadata import time_to_first_chunk_seconds
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from litellm.integrations.otel.model.semconv import Metric, resolve_operation
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from litellm.integrations.otel.model.utils import to_seconds
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from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
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@ -181,13 +182,10 @@ class GenAIMetricRecorder:
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self._metrics.token_usage.record(usage.get("completion_tokens", 0), attributes=out_attrs)
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def _record_time_to_first_token(self, kwargs: Mapping[str, Any], common_attrs: dict) -> None:
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if not kwargs.get("optional_params", {}).get("stream", False):
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time_to_first_chunk = time_to_first_chunk_seconds(kwargs)
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if time_to_first_chunk is None:
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return
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api_call_start = to_seconds(kwargs.get("api_call_start_time"))
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completion_start = to_seconds(kwargs.get("completion_start_time"))
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if api_call_start is None or completion_start is None:
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return
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self._metrics.time_to_first_token.record(completion_start - api_call_start, attributes=common_attrs)
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self._metrics.time_to_first_token.record(time_to_first_chunk, attributes=common_attrs)
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def _record_time_per_output_token(
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self,
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@ -168,6 +168,43 @@ def test_async_log_success_event_emits_llm_call_span():
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assert span.status.status_code is StatusCode.UNSET
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def test_streaming_span_carries_time_to_first_chunk():
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logger, exporter = _logger()
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kwargs = {
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**_kwargs(payload=_payload(stream=True)),
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"optional_params": {"stream": True},
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"api_call_start_time": datetime(2026, 5, 26, 12, 0, 0, tzinfo=timezone.utc),
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"completion_start_time": datetime(2026, 5, 26, 12, 0, 0, 750000, tzinfo=timezone.utc),
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}
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_emit_llm(logger, kwargs)
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(span,) = exporter.get_finished_spans()
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assert span.attributes[GenAI.RESPONSE_TIME_TO_FIRST_CHUNK] == pytest.approx(0.75)
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def test_non_streaming_span_has_no_time_to_first_chunk():
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logger, exporter = _logger()
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kwargs = {
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**_kwargs(),
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"optional_params": {},
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"api_call_start_time": datetime(2026, 5, 26, 12, 0, 0, tzinfo=timezone.utc),
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"completion_start_time": datetime(2026, 5, 26, 12, 0, 5, tzinfo=timezone.utc),
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}
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_emit_llm(logger, kwargs)
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(span,) = exporter.get_finished_spans()
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assert GenAI.RESPONSE_TIME_TO_FIRST_CHUNK not in span.attributes
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def test_streaming_span_without_timing_omits_time_to_first_chunk():
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logger, exporter = _logger()
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kwargs = {
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**_kwargs(payload=_payload(stream=True)),
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"optional_params": {"stream": True},
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}
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_emit_llm(logger, kwargs)
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(span,) = exporter.get_finished_spans()
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assert GenAI.RESPONSE_TIME_TO_FIRST_CHUNK not in span.attributes
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def test_async_log_failure_event_marks_error_status():
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logger, exporter = _logger()
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payload = _payload(
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