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https://github.com/meta-llama/llama-stack.git
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This PR adds two new methods to the telemetry API: 1) Gives the ability to query spans directly instead of first querying traces and then using that to get spans 2) Another method save_spans_to_dataset, which builds on the query spans to save it on dataset. This give the ability to saves spans that are part of an agent session to a dataset. The unique aspect of this API is that we dont require each provider of telemetry to implement this method. Hence, its implemented in the protocol class itself. This required the protocol check to be slightly modified.
205 lines
4.7 KiB
Python
205 lines
4.7 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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from datetime import datetime
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from enum import Enum
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from typing import (
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Any,
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Dict,
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List,
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Literal,
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Optional,
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Protocol,
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runtime_checkable,
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Union,
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)
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from llama_models.schema_utils import json_schema_type, webmethod
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from pydantic import BaseModel, Field
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from typing_extensions import Annotated
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# Add this constant near the top of the file, after the imports
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DEFAULT_TTL_DAYS = 7
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@json_schema_type
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class SpanStatus(Enum):
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OK = "ok"
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ERROR = "error"
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@json_schema_type
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class Span(BaseModel):
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span_id: str
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trace_id: str
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parent_span_id: Optional[str] = None
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name: str
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start_time: datetime
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end_time: Optional[datetime] = None
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attributes: Optional[Dict[str, Any]] = Field(default_factory=dict)
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def set_attribute(self, key: str, value: Any):
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if self.attributes is None:
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self.attributes = {}
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self.attributes[key] = value
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@json_schema_type
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class Trace(BaseModel):
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trace_id: str
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root_span_id: str
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start_time: datetime
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end_time: Optional[datetime] = None
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@json_schema_type
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class EventType(Enum):
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UNSTRUCTURED_LOG = "unstructured_log"
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STRUCTURED_LOG = "structured_log"
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METRIC = "metric"
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@json_schema_type
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class LogSeverity(Enum):
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VERBOSE = "verbose"
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DEBUG = "debug"
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INFO = "info"
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WARN = "warn"
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ERROR = "error"
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CRITICAL = "critical"
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class EventCommon(BaseModel):
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trace_id: str
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span_id: str
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timestamp: datetime
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attributes: Optional[Dict[str, Any]] = Field(default_factory=dict)
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@json_schema_type
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class UnstructuredLogEvent(EventCommon):
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type: Literal[EventType.UNSTRUCTURED_LOG.value] = EventType.UNSTRUCTURED_LOG.value
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message: str
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severity: LogSeverity
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@json_schema_type
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class MetricEvent(EventCommon):
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type: Literal[EventType.METRIC.value] = EventType.METRIC.value
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metric: str # this would be an enum
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value: Union[int, float]
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unit: str
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@json_schema_type
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class StructuredLogType(Enum):
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SPAN_START = "span_start"
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SPAN_END = "span_end"
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@json_schema_type
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class SpanStartPayload(BaseModel):
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type: Literal[StructuredLogType.SPAN_START.value] = (
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StructuredLogType.SPAN_START.value
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)
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name: str
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parent_span_id: Optional[str] = None
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@json_schema_type
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class SpanEndPayload(BaseModel):
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type: Literal[StructuredLogType.SPAN_END.value] = StructuredLogType.SPAN_END.value
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status: SpanStatus
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StructuredLogPayload = Annotated[
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Union[
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SpanStartPayload,
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SpanEndPayload,
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],
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Field(discriminator="type"),
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]
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@json_schema_type
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class StructuredLogEvent(EventCommon):
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type: Literal[EventType.STRUCTURED_LOG.value] = EventType.STRUCTURED_LOG.value
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payload: StructuredLogPayload
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Event = Annotated[
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Union[
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UnstructuredLogEvent,
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MetricEvent,
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StructuredLogEvent,
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],
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Field(discriminator="type"),
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]
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@json_schema_type
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class EvalTrace(BaseModel):
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session_id: str
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step: str
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input: str
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output: str
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expected_output: str
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@json_schema_type
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class SpanWithChildren(Span):
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children: List["SpanWithChildren"] = Field(default_factory=list)
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status: Optional[SpanStatus] = None
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@json_schema_type
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class QueryCondition(BaseModel):
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key: str
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op: Literal["eq", "ne", "gt", "lt"]
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value: Any
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@runtime_checkable
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class Telemetry(Protocol):
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@webmethod(route="/telemetry/log-event")
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async def log_event(
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self, event: Event, ttl_seconds: int = DEFAULT_TTL_DAYS * 86400
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) -> None: ...
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@webmethod(route="/telemetry/query-traces", method="POST")
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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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) -> List[Trace]: ...
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@webmethod(route="/telemetry/get-span-tree", method="POST")
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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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) -> SpanWithChildren: ...
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@webmethod(route="/telemetry/query-spans", method="POST")
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async def query_spans(
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self,
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attribute_filters: List[QueryCondition],
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attributes_to_return: List[str],
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max_depth: Optional[int] = None,
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) -> List[Span]: ...
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@webmethod(route="/telemetry/save-spans-to-dataset", method="POST")
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async def save_spans_to_dataset(
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self,
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attribute_filters: List[QueryCondition],
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attributes_to_save: List[str],
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dataset_id: str,
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max_depth: Optional[int] = None,
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) -> None: ...
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