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https://github.com/meta-llama/llama-stack.git
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# What does this PR do? This PR adds back the changes in #1300 which were reverted in #1476 . It also adds logic to preserve context variables across asyncio boundary. this is needed with the library client since the async generator logic yields control to code outside the event loop, and on resuming, does not have the same context as before and this requires preserving the context vars. address #1477 ## Test Plan ``` curl --request POST \ --url http://localhost:8321/v1/inference/chat-completion \ --header 'content-type: application/json' \ --data '{ "model_id": "meta-llama/Llama-3.1-70B-Instruct", "messages": [ { "role": "user", "content": { "type": "text", "text": "where do humans live" } } ], "stream": false }' | jq . { "metrics": [ { "trace_id": "kCZwO3tyQC-FuAGb", "span_id": "bsP_5a5O", "timestamp": "2025-03-11T16:47:38.549084Z", "attributes": { "model_id": "meta-llama/Llama-3.1-70B-Instruct", "provider_id": "fireworks" }, "type": "metric", "metric": "prompt_tokens", "value": 10, "unit": "tokens" }, { "trace_id": "kCZwO3tyQC-FuAGb", "span_id": "bsP_5a5O", "timestamp": "2025-03-11T16:47:38.549449Z", "attributes": { "model_id": "meta-llama/Llama-3.1-70B-Instruct", "provider_id": "fireworks" }, "type": "metric", "metric": "completion_tokens", "value": 369, "unit": "tokens" }, { "trace_id": "kCZwO3tyQC-FuAGb", "span_id": "bsP_5a5O", "timestamp": "2025-03-11T16:47:38.549457Z", "attributes": { "model_id": "meta-llama/Llama-3.1-70B-Instruct", "provider_id": "fireworks" }, "type": "metric", "metric": "total_tokens", "value": 379, "unit": "tokens" } ], "completion_message": { "role": "assistant", "content": "Humans live on the planet Earth, specifically on its landmasses and in its oceans. Here's a breakdown of where humans live:\n\n1. **Continents:** Humans inhabit all seven continents:\n\t* Africa\n\t* Antarctica ( temporary residents, mostly scientists and researchers)\n\t* Asia\n\t* Australia\n\t* Europe\n\t* North America\n\t* South America\n2. **Countries:** There are 196 countries recognized by the United Nations, and humans live in almost all of them.\n3. **Cities and towns:** Many humans live in urban areas, such as cities and towns, which are often located near coastlines, rivers, or other bodies of water.\n4. **Rural areas:** Some humans live in rural areas, such as villages, farms, and countryside.\n5. **Islands:** Humans inhabit many islands around the world, including those in the Pacific, Indian, and Atlantic Oceans.\n6. **Mountains and highlands:** Humans live in mountainous regions, such as the Himalayas, the Andes, and the Rocky Mountains.\n7. **Deserts:** Some humans live in desert regions, such as the Sahara, the Mojave, and the Atacama.\n8. **Coastal areas:** Many humans live in coastal areas, such as beaches, ports, and coastal cities.\n9. **Underwater habitats:** A few humans live in underwater habitats, such as research stations and submarines.\n10. **Space:** A small number of humans have lived in space, including astronauts on the International Space Station and those who have visited the Moon.\n\nOverall, humans can be found living in almost every environment on Earth, from the frozen tundra to the hottest deserts, and from the highest mountains to the deepest oceans.", "stop_reason": "end_of_turn", "tool_calls": [] }, "logprobs": null } ``` Orignal repro no longer showing any error: ``` LLAMA_STACK_DISABLE_VERSION_CHECK=true llama stack run ~/.llama/distributions/fireworks/fireworks-run.yaml python -m examples.agents.e2e_loop_with_client_tools localhost 8321 ``` client logs: https://gist.github.com/dineshyv/047c7e87b18a5792aa660e311ea53166 server logs: https://gist.github.com/dineshyv/97a2174099619e9916c7c490be26e559
274 lines
11 KiB
Python
274 lines
11 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import threading
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from typing import Any, Dict, List, Optional
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from opentelemetry import metrics, trace
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from opentelemetry.exporter.otlp.proto.http.metric_exporter import OTLPMetricExporter
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from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
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from opentelemetry.sdk.metrics import MeterProvider
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from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
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from opentelemetry.sdk.resources import Resource
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from opentelemetry.sdk.trace import TracerProvider
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from opentelemetry.sdk.trace.export import BatchSpanProcessor
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from opentelemetry.semconv.resource import ResourceAttributes
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from llama_stack.apis.telemetry import (
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Event,
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MetricEvent,
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QueryCondition,
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QuerySpanTreeResponse,
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QueryTracesResponse,
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Span,
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SpanEndPayload,
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SpanStartPayload,
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SpanStatus,
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StructuredLogEvent,
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Telemetry,
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Trace,
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UnstructuredLogEvent,
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)
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from llama_stack.distribution.datatypes import Api
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from llama_stack.providers.inline.telemetry.meta_reference.console_span_processor import (
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ConsoleSpanProcessor,
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)
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from llama_stack.providers.inline.telemetry.meta_reference.sqlite_span_processor import (
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SQLiteSpanProcessor,
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)
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from llama_stack.providers.utils.telemetry.dataset_mixin import TelemetryDatasetMixin
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from llama_stack.providers.utils.telemetry.sqlite_trace_store import SQLiteTraceStore
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from .config import TelemetryConfig, TelemetrySink
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_GLOBAL_STORAGE = {
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"active_spans": {},
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"counters": {},
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"gauges": {},
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"up_down_counters": {},
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}
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_global_lock = threading.Lock()
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_TRACER_PROVIDER = None
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def string_to_trace_id(s: str) -> int:
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# Convert the string to bytes and then to an integer
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return int.from_bytes(s.encode(), byteorder="big", signed=False)
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def string_to_span_id(s: str) -> int:
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# Use only the first 8 bytes (64 bits) for span ID
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return int.from_bytes(s.encode()[:8], byteorder="big", signed=False)
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def is_tracing_enabled(tracer):
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with tracer.start_as_current_span("check_tracing") as span:
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return span.is_recording()
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class TelemetryAdapter(TelemetryDatasetMixin, Telemetry):
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def __init__(self, config: TelemetryConfig, deps: Dict[str, Any]) -> None:
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self.config = config
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self.datasetio_api = deps.get(Api.datasetio)
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self.meter = None
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resource = Resource.create(
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{
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ResourceAttributes.SERVICE_NAME: self.config.service_name,
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}
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)
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global _TRACER_PROVIDER
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# Initialize the correct span processor based on the provider state.
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# This is needed since once the span processor is set, it cannot be unset.
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# Recreating the telemetry adapter multiple times will result in duplicate span processors.
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# Since the library client can be recreated multiple times in a notebook,
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# the kernel will hold on to the span processor and cause duplicate spans to be written.
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if _TRACER_PROVIDER is None:
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provider = TracerProvider(resource=resource)
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trace.set_tracer_provider(provider)
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_TRACER_PROVIDER = provider
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if TelemetrySink.OTEL in self.config.sinks:
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otlp_exporter = OTLPSpanExporter(
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endpoint=self.config.otel_endpoint,
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)
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span_processor = BatchSpanProcessor(otlp_exporter)
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trace.get_tracer_provider().add_span_processor(span_processor)
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metric_reader = PeriodicExportingMetricReader(
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OTLPMetricExporter(
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endpoint=self.config.otel_endpoint,
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)
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)
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metric_provider = MeterProvider(resource=resource, metric_readers=[metric_reader])
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metrics.set_meter_provider(metric_provider)
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if TelemetrySink.SQLITE in self.config.sinks:
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trace.get_tracer_provider().add_span_processor(SQLiteSpanProcessor(self.config.sqlite_db_path))
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if TelemetrySink.CONSOLE in self.config.sinks:
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trace.get_tracer_provider().add_span_processor(ConsoleSpanProcessor())
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if TelemetrySink.OTEL in self.config.sinks:
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self.meter = metrics.get_meter(__name__)
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if TelemetrySink.SQLITE in self.config.sinks:
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self.trace_store = SQLiteTraceStore(self.config.sqlite_db_path)
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self._lock = _global_lock
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async def initialize(self) -> None:
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pass
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async def shutdown(self) -> None:
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trace.get_tracer_provider().force_flush()
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async def log_event(self, event: Event, ttl_seconds: int = 604800) -> None:
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if isinstance(event, UnstructuredLogEvent):
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self._log_unstructured(event, ttl_seconds)
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elif isinstance(event, MetricEvent):
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self._log_metric(event)
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elif isinstance(event, StructuredLogEvent):
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self._log_structured(event, ttl_seconds)
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else:
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raise ValueError(f"Unknown event type: {event}")
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def _log_unstructured(self, event: UnstructuredLogEvent, ttl_seconds: int) -> None:
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with self._lock:
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# Use global storage instead of instance storage
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span_id = string_to_span_id(event.span_id)
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span = _GLOBAL_STORAGE["active_spans"].get(span_id)
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if span:
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timestamp_ns = int(event.timestamp.timestamp() * 1e9)
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span.add_event(
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name=event.type,
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attributes={
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"message": event.message,
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"severity": event.severity.value,
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"__ttl__": ttl_seconds,
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**event.attributes,
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},
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timestamp=timestamp_ns,
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)
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else:
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print(f"Warning: No active span found for span_id {span_id}. Dropping event: {event}")
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def _get_or_create_counter(self, name: str, unit: str) -> metrics.Counter:
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if name not in _GLOBAL_STORAGE["counters"]:
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_GLOBAL_STORAGE["counters"][name] = self.meter.create_counter(
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name=name,
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unit=unit,
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description=f"Counter for {name}",
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)
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return _GLOBAL_STORAGE["counters"][name]
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def _get_or_create_gauge(self, name: str, unit: str) -> metrics.ObservableGauge:
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if name not in _GLOBAL_STORAGE["gauges"]:
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_GLOBAL_STORAGE["gauges"][name] = self.meter.create_gauge(
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name=name,
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unit=unit,
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description=f"Gauge for {name}",
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)
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return _GLOBAL_STORAGE["gauges"][name]
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def _log_metric(self, event: MetricEvent) -> None:
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if self.meter is None:
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return
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if isinstance(event.value, int):
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counter = self._get_or_create_counter(event.metric, event.unit)
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counter.add(event.value, attributes=event.attributes)
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elif isinstance(event.value, float):
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up_down_counter = self._get_or_create_up_down_counter(event.metric, event.unit)
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up_down_counter.add(event.value, attributes=event.attributes)
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def _get_or_create_up_down_counter(self, name: str, unit: str) -> metrics.UpDownCounter:
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if name not in _GLOBAL_STORAGE["up_down_counters"]:
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_GLOBAL_STORAGE["up_down_counters"][name] = self.meter.create_up_down_counter(
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name=name,
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unit=unit,
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description=f"UpDownCounter for {name}",
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)
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return _GLOBAL_STORAGE["up_down_counters"][name]
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def _log_structured(self, event: StructuredLogEvent, ttl_seconds: int) -> None:
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with self._lock:
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span_id = string_to_span_id(event.span_id)
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trace_id = string_to_trace_id(event.trace_id)
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tracer = trace.get_tracer(__name__)
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if event.attributes is None:
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event.attributes = {}
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event.attributes["__ttl__"] = ttl_seconds
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if isinstance(event.payload, SpanStartPayload):
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# Check if span already exists to prevent duplicates
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if span_id in _GLOBAL_STORAGE["active_spans"]:
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return
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parent_span = None
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if event.payload.parent_span_id:
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parent_span_id = string_to_span_id(event.payload.parent_span_id)
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parent_span = _GLOBAL_STORAGE["active_spans"].get(parent_span_id)
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context = trace.Context(trace_id=trace_id)
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if parent_span:
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context = trace.set_span_in_context(parent_span, context)
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span = tracer.start_span(
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name=event.payload.name,
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context=context,
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attributes=event.attributes or {},
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)
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_GLOBAL_STORAGE["active_spans"][span_id] = span
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elif isinstance(event.payload, SpanEndPayload):
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span = _GLOBAL_STORAGE["active_spans"].get(span_id)
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if span:
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if event.attributes:
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span.set_attributes(event.attributes)
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status = (
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trace.Status(status_code=trace.StatusCode.OK)
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if event.payload.status == SpanStatus.OK
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else trace.Status(status_code=trace.StatusCode.ERROR)
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)
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span.set_status(status)
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span.end()
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_GLOBAL_STORAGE["active_spans"].pop(span_id, None)
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else:
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raise ValueError(f"Unknown structured log event: {event}")
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async def query_traces(
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self,
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attribute_filters: Optional[List[QueryCondition]] = None,
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limit: Optional[int] = 100,
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offset: Optional[int] = 0,
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order_by: Optional[List[str]] = None,
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) -> QueryTracesResponse:
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return QueryTracesResponse(
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data=await self.trace_store.query_traces(
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attribute_filters=attribute_filters,
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limit=limit,
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offset=offset,
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order_by=order_by,
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)
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)
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async def get_trace(self, trace_id: str) -> Trace:
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return await self.trace_store.get_trace(trace_id)
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async def get_span(self, trace_id: str, span_id: str) -> Span:
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return await self.trace_store.get_span(trace_id, span_id)
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async def get_span_tree(
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self,
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span_id: str,
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attributes_to_return: Optional[List[str]] = None,
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max_depth: Optional[int] = None,
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) -> QuerySpanTreeResponse:
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return QuerySpanTreeResponse(
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data=await self.trace_store.get_span_tree(
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span_id=span_id,
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attributes_to_return=attributes_to_return,
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max_depth=max_depth,
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)
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)
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