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feat: make telemetry attributes be dict[str,PrimitiveType] (#1055)
# What does this PR do? Make attributes in telemetry be only primitive types and avoid arbitrary nesting. ## Test Plan ``` LLAMA_STACK_DISABLE_VERSION_CHECK=true llama stack run ~/.llama/distributions/fireworks/fireworks-run.yaml LLAMA_STACK_BASE_URL=http://localhost:8321 pytest -v tests/client-sdk/agents/test_agents.py -k "test_builtin_tool_web_search" # Verified that attributes still show up correclty in jaeger ```
This commit is contained in:
Dinesh Yeduguru
GitHub
parent
ab7f802698
commit
d8a20e034b
4 changed files with 29 additions and 45 deletions
36
docs/_static/llama-stack-spec.html
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@ -3148,22 +3148,19 @@
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"additionalProperties": {
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"oneOf": [
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{
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"type": "null"
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"type": "string"
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},
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{
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"type": "boolean"
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"type": "integer"
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},
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{
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"type": "number"
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},
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{
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"type": "string"
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"type": "boolean"
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},
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{
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"type": "array"
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},
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{
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"type": "object"
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"type": "null"
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}
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]
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}
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@ -3683,8 +3680,7 @@
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"auto",
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"required"
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],
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"description": "Whether tool use is required or automatic. This is a hint to the model which may not be followed. It depends on the Instruction Following capabilities of the model.",
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"default": "auto"
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"description": "Whether tool use is required or automatic. This is a hint to the model which may not be followed. It depends on the Instruction Following capabilities of the model."
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},
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"tool_prompt_format": {
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"type": "string",
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@ -6514,22 +6510,19 @@
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"additionalProperties": {
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"oneOf": [
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{
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"type": "null"
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"type": "string"
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},
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{
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"type": "boolean"
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"type": "integer"
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},
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{
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"type": "number"
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},
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{
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"type": "string"
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"type": "boolean"
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},
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{
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"type": "array"
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},
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{
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"type": "object"
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"type": "null"
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}
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]
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}
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@ -6587,22 +6580,19 @@
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"additionalProperties": {
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"oneOf": [
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{
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"type": "null"
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"type": "string"
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},
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{
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"type": "boolean"
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"type": "integer"
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},
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{
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"type": "number"
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},
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{
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"type": "string"
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"type": "boolean"
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},
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{
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"type": "array"
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},
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{
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"type": "object"
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"type": "null"
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}
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]
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}
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28
docs/_static/llama-stack-spec.yaml
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@ -1956,12 +1956,11 @@ components:
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type: object
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additionalProperties:
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oneOf:
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- type: 'null'
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- type: boolean
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- type: number
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- type: string
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- type: array
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- type: object
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- type: integer
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- type: number
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- type: boolean
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- type: 'null'
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type:
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type: string
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const: metric
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@ -2387,7 +2386,6 @@ components:
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Whether tool use is required or automatic. This is a hint to the model
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which may not be followed. It depends on the Instruction Following capabilities
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of the model.
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default: auto
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tool_prompt_format:
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type: string
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enum:
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@ -4161,12 +4159,11 @@ components:
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type: object
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additionalProperties:
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oneOf:
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- type: 'null'
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- type: boolean
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- type: number
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- type: string
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- type: array
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- type: object
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- type: integer
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- type: number
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- type: boolean
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- type: 'null'
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type:
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type: string
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const: structured_log
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@ -4203,12 +4200,11 @@ components:
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type: object
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additionalProperties:
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oneOf:
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- type: 'null'
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- type: boolean
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- type: number
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- type: string
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- type: array
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- type: object
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- type: integer
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- type: number
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- type: boolean
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- type: 'null'
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type:
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type: string
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const: unstructured_log
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@ -17,6 +17,7 @@ from typing import (
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runtime_checkable,
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)
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from llama_models.llama3.api.datatypes import Primitive
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from llama_models.schema_utils import json_schema_type, register_schema, webmethod
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from pydantic import BaseModel, Field
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from typing_extensions import Annotated
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@ -76,7 +77,7 @@ 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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attributes: Optional[Dict[str, Primitive]] = Field(default_factory=dict)
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@json_schema_type
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@ -9,12 +9,13 @@ import inspect
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from functools import wraps
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from typing import Any, AsyncGenerator, Callable, Type, TypeVar
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from llama_models.llama3.api.datatypes import Primitive
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from pydantic import BaseModel
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T = TypeVar("T")
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def serialize_value(value: Any) -> Any:
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def serialize_value(value: Any) -> Primitive:
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"""Serialize a single value into JSON-compatible format."""
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if value is None:
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return ""
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@ -24,10 +25,6 @@ def serialize_value(value: Any) -> Any:
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return value._name_
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elif isinstance(value, BaseModel):
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return value.model_dump_json()
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elif isinstance(value, (list, tuple, set)):
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return [serialize_value(item) for item in value]
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elif isinstance(value, dict):
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return {str(k): serialize_value(v) for k, v in value.items()}
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else:
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return str(value)
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