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Telemetry API redesign (#525)

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# What does this PR do?
Change the Telemetry API to be able to support different use cases like
returning traces for the UI and ability to export for Evals.
Other changes:
* Add a new trace_protocol decorator to decorate all our API methods so
that any call to them will automatically get traced across all impls.
* There is some issue with the decorator pattern of span creation when
using async generators, where there are multiple yields with in the same
context. I think its much more explicit by using the explicit context
manager pattern using with. I moved the span creations in agent instance
to be using with
* Inject session id at the turn level, which should quickly give us all
traces across turns for a given session

Addresses #509

## Test Plan
```
llama stack run /Users/dineshyv/.llama/distributions/llamastack-together/together-run.yaml
PYTHONPATH=. python -m examples.agents.rag_with_memory_bank localhost 5000


 curl -X POST 'http://localhost:5000/alpha/telemetry/query-traces' \
-H 'Content-Type: application/json' \
-d '{
  "attribute_filters": [
    {
      "key": "session_id",
      "op": "eq",
      "value": "dd667b87-ca4b-4d30-9265-5a0de318fc65" }],
  "limit": 100,
  "offset": 0,
  "order_by": ["start_time"]
}' | jq .
[
  {
    "trace_id": "6902f54b83b4b48be18a6f422b13e16f",
    "root_span_id": "5f37b85543afc15a",
    "start_time": "2024-12-04T08:08:30.501587",
    "end_time": "2024-12-04T08:08:36.026463"
  },
  {
    "trace_id": "92227dac84c0615ed741be393813fb5f",
    "root_span_id": "af7c5bb46665c2c8",
    "start_time": "2024-12-04T08:08:36.031170",
    "end_time": "2024-12-04T08:08:41.693301"
  },
  {
    "trace_id": "7d578a6edac62f204ab479fba82f77b6",
    "root_span_id": "1d935e3362676896",
    "start_time": "2024-12-04T08:08:41.695204",
    "end_time": "2024-12-04T08:08:47.228016"
  },
  {
    "trace_id": "dbd767d76991bc816f9f078907dc9ff2",
    "root_span_id": "f5a7ee76683b9602",
    "start_time": "2024-12-04T08:08:47.234578",
    "end_time": "2024-12-04T08:08:53.189412"
  }
]


curl -X POST 'http://localhost:5000/alpha/telemetry/get-span-tree' \
-H 'Content-Type: application/json' \
-d '{ "span_id" : "6cceb4b48a156913", "max_depth": 2, "attributes_to_return": ["input"] }' | jq .
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100   875  100   790  100    85  18462   1986 --:--:-- --:--:-- --:--:-- 20833
{
  "span_id": "6cceb4b48a156913",
  "trace_id": "dafa796f6aaf925f511c04cd7c67fdda",
  "parent_span_id": "892a66d726c7f990",
  "name": "retrieve_rag_context",
  "start_time": "2024-12-04T09:28:21.781995",
  "end_time": "2024-12-04T09:28:21.913352",
  "attributes": {
    "input": [
      "{\"role\":\"system\",\"content\":\"You are a helpful assistant\"}",
      "{\"role\":\"user\",\"content\":\"What are the top 5 topics that were explained in the documentation? Only list succinct bullet points.\",\"context\":null}"
    ]
  },
  "children": [
    {
      "span_id": "1a2df181854064a8",
      "trace_id": "dafa796f6aaf925f511c04cd7c67fdda",
      "parent_span_id": "6cceb4b48a156913",
      "name": "MemoryRouter.query_documents",
      "start_time": "2024-12-04T09:28:21.787620",
      "end_time": "2024-12-04T09:28:21.906512",
      "attributes": {
        "input": null
      },
      "children": [],
      "status": "ok"
    }
  ],
  "status": "ok"
}

```

<img width="1677" alt="Screenshot 2024-12-04 at 9 42 56 AM"
src="https://github.com/user-attachments/assets/4d3cea93-05ce-415a-93d9-4b1628631bf8">
This commit is contained in:
Dinesh Yeduguru 2024-12-04 11:22:45 -08:00 • committed by GitHub
parent 16769256b7
commit fcd6449519
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llama_stack/providers/inline/telemetry/meta_reference/telemetry.py Normal file
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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import threading
from typing import List, Optional
from opentelemetry import metrics, trace
from opentelemetry.exporter.otlp.proto.http.metric_exporter import OTLPMetricExporter
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.semconv.resource import ResourceAttributes
from llama_stack.providers.inline.telemetry.meta_reference.console_span_processor import (
ConsoleSpanProcessor,
)
from llama_stack.providers.inline.telemetry.meta_reference.sqlite_span_processor import (
SQLiteSpanProcessor,
)
from llama_stack.providers.utils.telemetry.sqlite_trace_store import SQLiteTraceStore
from llama_stack.apis.telemetry import * # noqa: F403
from .config import TelemetryConfig, TelemetrySink
_GLOBAL_STORAGE = {
"active_spans": {},
"counters": {},
"gauges": {},
"up_down_counters": {},
}
_global_lock = threading.Lock()
def string_to_trace_id(s: str) -> int:
# Convert the string to bytes and then to an integer
return int.from_bytes(s.encode(), byteorder="big", signed=False)
def string_to_span_id(s: str) -> int:
# Use only the first 8 bytes (64 bits) for span ID
return int.from_bytes(s.encode()[:8], byteorder="big", signed=False)
def is_tracing_enabled(tracer):
with tracer.start_as_current_span("check_tracing") as span:
return span.is_recording()
class TelemetryAdapter(Telemetry):
def __init__(self, config: TelemetryConfig) -> None:
self.config = config
resource = Resource.create(
{
ResourceAttributes.SERVICE_NAME: self.config.service_name,
}
)
provider = TracerProvider(resource=resource)
trace.set_tracer_provider(provider)
if TelemetrySink.JAEGER in self.config.sinks:
otlp_exporter = OTLPSpanExporter(
endpoint=self.config.otel_endpoint,
)
span_processor = BatchSpanProcessor(otlp_exporter)
trace.get_tracer_provider().add_span_processor(span_processor)
metric_reader = PeriodicExportingMetricReader(
OTLPMetricExporter(
endpoint=self.config.otel_endpoint,
)
)
metric_provider = MeterProvider(
resource=resource, metric_readers=[metric_reader]
)
metrics.set_meter_provider(metric_provider)
self.meter = metrics.get_meter(__name__)
if TelemetrySink.SQLITE in self.config.sinks:
trace.get_tracer_provider().add_span_processor(
SQLiteSpanProcessor(self.config.sqlite_db_path)
)
self.trace_store = SQLiteTraceStore(self.config.sqlite_db_path)
if TelemetrySink.CONSOLE in self.config.sinks:
trace.get_tracer_provider().add_span_processor(ConsoleSpanProcessor())
self._lock = _global_lock
async def initialize(self) -> None:
pass
async def shutdown(self) -> None:
trace.get_tracer_provider().force_flush()
trace.get_tracer_provider().shutdown()
metrics.get_meter_provider().shutdown()
async def log_event(self, event: Event, ttl_seconds: int = 604800) -> None:
if isinstance(event, UnstructuredLogEvent):
self._log_unstructured(event, ttl_seconds)
elif isinstance(event, MetricEvent):
self._log_metric(event)
elif isinstance(event, StructuredLogEvent):
self._log_structured(event, ttl_seconds)
else:
raise ValueError(f"Unknown event type: {event}")
def _log_unstructured(self, event: UnstructuredLogEvent, ttl_seconds: int) -> None:
with self._lock:
# Use global storage instead of instance storage
span_id = string_to_span_id(event.span_id)
span = _GLOBAL_STORAGE["active_spans"].get(span_id)
if span:
timestamp_ns = int(event.timestamp.timestamp() * 1e9)
span.add_event(
name=event.type,
attributes={
"message": event.message,
"severity": event.severity.value,
"__ttl__": ttl_seconds,
**event.attributes,
},
timestamp=timestamp_ns,
)
else:
print(
f"Warning: No active span found for span_id {span_id}. Dropping event: {event}"
)
def _get_or_create_counter(self, name: str, unit: str) -> metrics.Counter:
if name not in _GLOBAL_STORAGE["counters"]:
_GLOBAL_STORAGE["counters"][name] = self.meter.create_counter(
name=name,
unit=unit,
description=f"Counter for {name}",
)
return _GLOBAL_STORAGE["counters"][name]
def _get_or_create_gauge(self, name: str, unit: str) -> metrics.ObservableGauge:
if name not in _GLOBAL_STORAGE["gauges"]:
_GLOBAL_STORAGE["gauges"][name] = self.meter.create_gauge(
name=name,
unit=unit,
description=f"Gauge for {name}",
)
return _GLOBAL_STORAGE["gauges"][name]
def _log_metric(self, event: MetricEvent) -> None:
if isinstance(event.value, int):
counter = self._get_or_create_counter(event.metric, event.unit)
counter.add(event.value, attributes=event.attributes)
elif isinstance(event.value, float):
up_down_counter = self._get_or_create_up_down_counter(
event.metric, event.unit
)
up_down_counter.add(event.value, attributes=event.attributes)
def _get_or_create_up_down_counter(
self, name: str, unit: str
) -> metrics.UpDownCounter:
if name not in _GLOBAL_STORAGE["up_down_counters"]:
_GLOBAL_STORAGE["up_down_counters"][name] = (
self.meter.create_up_down_counter(
name=name,
unit=unit,
description=f"UpDownCounter for {name}",
)
)
return _GLOBAL_STORAGE["up_down_counters"][name]
def _log_structured(self, event: StructuredLogEvent, ttl_seconds: int) -> None:
with self._lock:
span_id = string_to_span_id(event.span_id)
trace_id = string_to_trace_id(event.trace_id)
tracer = trace.get_tracer(__name__)
if event.attributes is None:
event.attributes = {}
event.attributes["__ttl__"] = ttl_seconds
if isinstance(event.payload, SpanStartPayload):
# Check if span already exists to prevent duplicates
if span_id in _GLOBAL_STORAGE["active_spans"]:
return
parent_span = None
if event.payload.parent_span_id:
parent_span_id = string_to_span_id(event.payload.parent_span_id)
parent_span = _GLOBAL_STORAGE["active_spans"].get(parent_span_id)
context = trace.Context(trace_id=trace_id)
if parent_span:
context = trace.set_span_in_context(parent_span, context)
span = tracer.start_span(
name=event.payload.name,
context=context,
attributes=event.attributes or {},
)
_GLOBAL_STORAGE["active_spans"][span_id] = span
elif isinstance(event.payload, SpanEndPayload):
span = _GLOBAL_STORAGE["active_spans"].get(span_id)
if span:
if event.attributes:
span.set_attributes(event.attributes)
status = (
trace.Status(status_code=trace.StatusCode.OK)
if event.payload.status == SpanStatus.OK
else trace.Status(status_code=trace.StatusCode.ERROR)
)
span.set_status(status)
span.end()
_GLOBAL_STORAGE["active_spans"].pop(span_id, None)
else:
raise ValueError(f"Unknown structured log event: {event}")
async def query_traces(
self,
attribute_filters: Optional[List[QueryCondition]] = None,
limit: Optional[int] = 100,
offset: Optional[int] = 0,
order_by: Optional[List[str]] = None,
) -> List[Trace]:
return await self.trace_store.query_traces(
attribute_filters=attribute_filters,
limit=limit,
offset=offset,
order_by=order_by,
)
async def get_span_tree(
self,
span_id: str,
attributes_to_return: Optional[List[str]] = None,
max_depth: Optional[int] = None,
) -> SpanWithChildren:
return await self.trace_store.get_materialized_span(
span_id=span_id,
attributes_to_return=attributes_to_return,
max_depth=max_depth,
)