llama-stack-mirror/llama_stack/apis/telemetry/telemetry.py

531 lines
16 KiB
Python

# 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.
from datetime import datetime
from enum import Enum
from typing import (
Annotated,
Any,
Literal,
Protocol,
runtime_checkable,
)
from pydantic import BaseModel, Field
from llama_stack.models.llama.datatypes import Primitive
from llama_stack.schema_utils import json_schema_type, register_schema, webmethod
# Add this constant near the top of the file, after the imports
DEFAULT_TTL_DAYS = 7
@json_schema_type
class SpanStatus(Enum):
"""The status of a span indicating whether it completed successfully or with an error.
:cvar OK: Span completed successfully without errors
:cvar ERROR: Span completed with an error or failure
"""
OK = "ok"
ERROR = "error"
@json_schema_type
class Span(BaseModel):
"""A span representing a single operation within a trace.
:param span_id: Unique identifier for the span
:param trace_id: Unique identifier for the trace this span belongs to
:param parent_span_id: (Optional) Unique identifier for the parent span, if this is a child span
:param name: Human-readable name describing the operation this span represents
:param start_time: Timestamp when the operation began
:param end_time: (Optional) Timestamp when the operation finished, if completed
:param attributes: (Optional) Key-value pairs containing additional metadata about the span
"""
span_id: str
trace_id: str
parent_span_id: str | None = None
name: str
start_time: datetime
end_time: datetime | None = None
attributes: dict[str, Any] | None = Field(default_factory=lambda: {})
def set_attribute(self, key: str, value: Any):
if self.attributes is None:
self.attributes = {}
self.attributes[key] = value
@json_schema_type
class Trace(BaseModel):
"""A trace representing the complete execution path of a request across multiple operations.
:param trace_id: Unique identifier for the trace
:param root_span_id: Unique identifier for the root span that started this trace
:param start_time: Timestamp when the trace began
:param end_time: (Optional) Timestamp when the trace finished, if completed
"""
trace_id: str
root_span_id: str
start_time: datetime
end_time: datetime | None = None
@json_schema_type
class EventType(Enum):
"""The type of telemetry event being logged.
:cvar UNSTRUCTURED_LOG: A simple log message with severity level
:cvar STRUCTURED_LOG: A structured log event with typed payload data
:cvar METRIC: A metric measurement with value and unit
"""
UNSTRUCTURED_LOG = "unstructured_log"
STRUCTURED_LOG = "structured_log"
METRIC = "metric"
@json_schema_type
class LogSeverity(Enum):
"""The severity level of a log message.
:cvar VERBOSE: Detailed diagnostic information for troubleshooting
:cvar DEBUG: Debug information useful during development
:cvar INFO: General informational messages about normal operation
:cvar WARN: Warning messages about potentially problematic situations
:cvar ERROR: Error messages indicating failures that don't stop execution
:cvar CRITICAL: Critical error messages indicating severe failures
"""
VERBOSE = "verbose"
DEBUG = "debug"
INFO = "info"
WARN = "warn"
ERROR = "error"
CRITICAL = "critical"
class EventCommon(BaseModel):
"""Common fields shared by all telemetry events.
:param trace_id: Unique identifier for the trace this event belongs to
:param span_id: Unique identifier for the span this event belongs to
:param timestamp: Timestamp when the event occurred
:param attributes: (Optional) Key-value pairs containing additional metadata about the event
"""
trace_id: str
span_id: str
timestamp: datetime
attributes: dict[str, Primitive] | None = Field(default_factory=lambda: {})
@json_schema_type
class UnstructuredLogEvent(EventCommon):
"""An unstructured log event containing a simple text message.
:param type: Event type identifier set to UNSTRUCTURED_LOG
:param message: The log message text
:param severity: The severity level of the log message
"""
type: Literal[EventType.UNSTRUCTURED_LOG] = EventType.UNSTRUCTURED_LOG
message: str
severity: LogSeverity
@json_schema_type
class MetricEvent(EventCommon):
"""A metric event containing a measured value.
:param type: Event type identifier set to METRIC
:param metric: The name of the metric being measured
:param value: The numeric value of the metric measurement
:param unit: The unit of measurement for the metric value
"""
type: Literal[EventType.METRIC] = EventType.METRIC
metric: str # this would be an enum
value: int | float
unit: str
@json_schema_type
class MetricInResponse(BaseModel):
"""A metric value included in API responses.
:param metric: The name of the metric
:param value: The numeric value of the metric
:param unit: (Optional) The unit of measurement for the metric value
"""
metric: str
value: int | float
unit: str | None = None
# This is a short term solution to allow inference API to return metrics
# The ideal way to do this is to have a way for all response types to include metrics
# and all metric events logged to the telemetry API to be included with the response
# To do this, we will need to augment all response types with a metrics field.
# We have hit a blocker from stainless SDK that prevents us from doing this.
# The blocker is that if we were to augment the response types that have a data field
# in them like so
# class ListModelsResponse(BaseModel):
# metrics: Optional[List[MetricEvent]] = None
# data: List[Models]
# ...
# The client SDK will need to access the data by using a .data field, which is not
# ergonomic. Stainless SDK does support unwrapping the response type, but it
# requires that the response type to only have a single field.
# We will need a way in the client SDK to signal that the metrics are needed
# and if they are needed, the client SDK has to return the full response type
# without unwrapping it.
class MetricResponseMixin(BaseModel):
"""Mixin class for API responses that can include metrics.
:param metrics: (Optional) List of metrics associated with the API response
"""
metrics: list[MetricInResponse] | None = None
@json_schema_type
class StructuredLogType(Enum):
"""The type of structured log event payload.
:cvar SPAN_START: Event indicating the start of a new span
:cvar SPAN_END: Event indicating the completion of a span
"""
SPAN_START = "span_start"
SPAN_END = "span_end"
@json_schema_type
class SpanStartPayload(BaseModel):
"""Payload for a span start event.
:param type: Payload type identifier set to SPAN_START
:param name: Human-readable name describing the operation this span represents
:param parent_span_id: (Optional) Unique identifier for the parent span, if this is a child span
"""
type: Literal[StructuredLogType.SPAN_START] = StructuredLogType.SPAN_START
name: str
parent_span_id: str | None = None
@json_schema_type
class SpanEndPayload(BaseModel):
"""Payload for a span end event.
:param type: Payload type identifier set to SPAN_END
:param status: The final status of the span indicating success or failure
"""
type: Literal[StructuredLogType.SPAN_END] = StructuredLogType.SPAN_END
status: SpanStatus
StructuredLogPayload = Annotated[
SpanStartPayload | SpanEndPayload,
Field(discriminator="type"),
]
register_schema(StructuredLogPayload, name="StructuredLogPayload")
@json_schema_type
class StructuredLogEvent(EventCommon):
"""A structured log event containing typed payload data.
:param type: Event type identifier set to STRUCTURED_LOG
:param payload: The structured payload data for the log event
"""
type: Literal[EventType.STRUCTURED_LOG] = EventType.STRUCTURED_LOG
payload: StructuredLogPayload
Event = Annotated[
UnstructuredLogEvent | MetricEvent | StructuredLogEvent,
Field(discriminator="type"),
]
register_schema(Event, name="Event")
@json_schema_type
class EvalTrace(BaseModel):
"""A trace record for evaluation purposes.
:param session_id: Unique identifier for the evaluation session
:param step: The evaluation step or phase identifier
:param input: The input data for the evaluation
:param output: The actual output produced during evaluation
:param expected_output: The expected output for comparison during evaluation
"""
session_id: str
step: str
input: str
output: str
expected_output: str
@json_schema_type
class SpanWithStatus(Span):
"""A span that includes status information.
:param status: (Optional) The current status of the span
"""
status: SpanStatus | None = None
@json_schema_type
class QueryConditionOp(Enum):
"""Comparison operators for query conditions.
:cvar EQ: Equal to comparison
:cvar NE: Not equal to comparison
:cvar GT: Greater than comparison
:cvar LT: Less than comparison
"""
EQ = "eq"
NE = "ne"
GT = "gt"
LT = "lt"
@json_schema_type
class QueryCondition(BaseModel):
"""A condition for filtering query results.
:param key: The attribute key to filter on
:param op: The comparison operator to apply
:param value: The value to compare against
"""
key: str
op: QueryConditionOp
value: Any
class QueryTracesResponse(BaseModel):
"""Response containing a list of traces.
:param data: List of traces matching the query criteria
"""
data: list[Trace]
class QuerySpansResponse(BaseModel):
"""Response containing a list of spans.
:param data: List of spans matching the query criteria
"""
data: list[Span]
class QuerySpanTreeResponse(BaseModel):
"""Response containing a tree structure of spans.
:param data: Dictionary mapping span IDs to spans with status information
"""
data: dict[str, SpanWithStatus]
class MetricQueryType(Enum):
"""The type of metric query to perform.
:cvar RANGE: Query metrics over a time range
:cvar INSTANT: Query metrics at a specific point in time
"""
RANGE = "range"
INSTANT = "instant"
class MetricLabelOperator(Enum):
"""Operators for matching metric labels.
:cvar EQUALS: Label value must equal the specified value
:cvar NOT_EQUALS: Label value must not equal the specified value
:cvar REGEX_MATCH: Label value must match the specified regular expression
:cvar REGEX_NOT_MATCH: Label value must not match the specified regular expression
"""
EQUALS = "="
NOT_EQUALS = "!="
REGEX_MATCH = "=~"
REGEX_NOT_MATCH = "!~"
class MetricLabelMatcher(BaseModel):
"""A matcher for filtering metrics by label values.
:param name: The name of the label to match
:param value: The value to match against
:param operator: The comparison operator to use for matching
"""
name: str
value: str
operator: MetricLabelOperator = MetricLabelOperator.EQUALS
@json_schema_type
class MetricLabel(BaseModel):
"""A label associated with a metric.
:param name: The name of the label
:param value: The value of the label
"""
name: str
value: str
@json_schema_type
class MetricDataPoint(BaseModel):
"""A single data point in a metric time series.
:param timestamp: Unix timestamp when the metric value was recorded
:param value: The numeric value of the metric at this timestamp
"""
timestamp: int
value: float
@json_schema_type
class MetricSeries(BaseModel):
"""A time series of metric data points.
:param metric: The name of the metric
:param labels: List of labels associated with this metric series
:param values: List of data points in chronological order
"""
metric: str
labels: list[MetricLabel]
values: list[MetricDataPoint]
class QueryMetricsResponse(BaseModel):
"""Response containing metric time series data.
:param data: List of metric series matching the query criteria
"""
data: list[MetricSeries]
@runtime_checkable
class Telemetry(Protocol):
@webmethod(route="/telemetry/events", method="POST")
async def log_event(
self,
event: Event,
ttl_seconds: int = DEFAULT_TTL_DAYS * 86400,
) -> None:
"""Log an event.
:param event: The event to log.
:param ttl_seconds: The time to live of the event.
"""
...
@webmethod(route="/telemetry/traces", method="POST")
async def query_traces(
self,
attribute_filters: list[QueryCondition] | None = None,
limit: int | None = 100,
offset: int | None = 0,
order_by: list[str] | None = None,
) -> QueryTracesResponse:
"""Query traces.
:param attribute_filters: The attribute filters to apply to the traces.
:param limit: The limit of traces to return.
:param offset: The offset of the traces to return.
:param order_by: The order by of the traces to return.
:returns: A QueryTracesResponse.
"""
...
@webmethod(route="/telemetry/traces/{trace_id:path}", method="GET")
async def get_trace(self, trace_id: str) -> Trace:
"""Get a trace by its ID.
:param trace_id: The ID of the trace to get.
:returns: A Trace.
"""
...
@webmethod(route="/telemetry/traces/{trace_id:path}/spans/{span_id:path}", method="GET")
async def get_span(self, trace_id: str, span_id: str) -> Span:
"""Get a span by its ID.
:param trace_id: The ID of the trace to get the span from.
:param span_id: The ID of the span to get.
:returns: A Span.
"""
...
@webmethod(route="/telemetry/spans/{span_id:path}/tree", method="POST")
async def get_span_tree(
self,
span_id: str,
attributes_to_return: list[str] | None = None,
max_depth: int | None = None,
) -> QuerySpanTreeResponse:
"""Get a span tree by its ID.
:param span_id: The ID of the span to get the tree from.
:param attributes_to_return: The attributes to return in the tree.
:param max_depth: The maximum depth of the tree.
:returns: A QuerySpanTreeResponse.
"""
...
@webmethod(route="/telemetry/spans", method="POST")
async def query_spans(
self,
attribute_filters: list[QueryCondition],
attributes_to_return: list[str],
max_depth: int | None = None,
) -> QuerySpansResponse:
"""Query spans.
:param attribute_filters: The attribute filters to apply to the spans.
:param attributes_to_return: The attributes to return in the spans.
:param max_depth: The maximum depth of the tree.
:returns: A QuerySpansResponse.
"""
...
@webmethod(route="/telemetry/spans/export", method="POST")
async def save_spans_to_dataset(
self,
attribute_filters: list[QueryCondition],
attributes_to_save: list[str],
dataset_id: str,
max_depth: int | None = None,
) -> None:
"""Save spans to a dataset.
:param attribute_filters: The attribute filters to apply to the spans.
:param attributes_to_save: The attributes to save to the dataset.
:param dataset_id: The ID of the dataset to save the spans to.
:param max_depth: The maximum depth of the tree.
"""
...
@webmethod(route="/telemetry/metrics/{metric_name}", method="POST")
async def query_metrics(
self,
metric_name: str,
start_time: int,
end_time: int | None = None,
granularity: str | None = "1d",
query_type: MetricQueryType = MetricQueryType.RANGE,
label_matchers: list[MetricLabelMatcher] | None = None,
) -> QueryMetricsResponse:
"""Query metrics.
:param metric_name: The name of the metric to query.
:param start_time: The start time of the metric to query.
:param end_time: The end time of the metric to query.
:param granularity: The granularity of the metric to query.
:param query_type: The type of query to perform.
:param label_matchers: The label matchers to apply to the metric.
:returns: A QueryMetricsResponse.
"""
...