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chore: import upstream snapshot with attribution
2026-07-13 13:25:13 +08:00

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# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Hand-written expected telemetry shapes for the node/workflow functional
tests.
Each ``EXPECTED_*`` is a complete ``SpanDigest`` tree (with per-span
``LogDigest`` lists nested in) describing what telemetry the canonical
Workflow + node + agent + tool + 2-LLM-turn scenario should emit under one
specific combination of:
* ``OTEL_SEMCONV_STABILITY_OPT_IN``
* ``OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT``
The cases are deliberately repetitive and verbose. The point is to give
"at-a-glance" visibility into what telemetry should look like under each
config -- DO NOT factor the construction into helpers.
"""
from __future__ import annotations
from .functional_test_helpers import AGENT_DESCRIPTION
from .functional_test_helpers import AGENT_NAME
from .functional_test_helpers import BASE_INSTRUCTION
from .functional_test_helpers import EXPERIMENTAL_OPT_IN
from .functional_test_helpers import FINAL_TEXT
from .functional_test_helpers import FunctionalTestCase
from .functional_test_helpers import GEN_AI_CHOICE_EVENT
from .functional_test_helpers import GEN_AI_COMPLETION_DETAILS_EVENT
from .functional_test_helpers import GEN_AI_SYSTEM_MESSAGE_EVENT
from .functional_test_helpers import GEN_AI_USER_MESSAGE_EVENT
from .functional_test_helpers import LogDigest
from .functional_test_helpers import MetricPoint
from .functional_test_helpers import NESTED_WORKFLOW_NAME
from .functional_test_helpers import NODE_NAME
from .functional_test_helpers import NODE_RESULT
from .functional_test_helpers import NON_DETERMINISTIC
from .functional_test_helpers import PRESENT
from .functional_test_helpers import SpanDigest
from .functional_test_helpers import TelemetryDigest
from .functional_test_helpers import TOOL_ARGS
from .functional_test_helpers import TOOL_DESCRIPTION
from .functional_test_helpers import TOOL_NAME
from .functional_test_helpers import TOOL_RESULT
from .functional_test_helpers import USER_PROMPT
from .functional_test_helpers import WORKFLOW_NAME
# The agent's "user" input in this scenario is the node's output, since
# the workflow runs `START -> some_node -> agent`.
_AGENT_USER_INPUT = NODE_RESULT
# In the node scenario the agent is not the runner's root, so ADK does not
# auto-append identity info to the system instruction.
_NODE_SYSTEM_INSTRUCTION = BASE_INSTRUCTION
# ---------------------------------------------------------------------------
# Stable semconv, OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=false
# ---------------------------------------------------------------------------
EXPECTED_STABLE_NO_CAPTURE_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.system": "gemini",
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
},
logs=[
LogDigest(
event_name=GEN_AI_CHOICE_EVENT,
body={
"content": "<elided>",
"index": 0,
"finish_reason": "STOP",
},
attributes={
"gen_ai.system": "gemini"
},
),
LogDigest(
event_name=GEN_AI_SYSTEM_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={
"gen_ai.system": "gemini"
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={
"gen_ai.system": "gemini"
},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": (
"execute_tool"
),
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": (
"FunctionTool"
),
"gcp.vertex.agent.llm_request": (
"{}"
),
"gcp.vertex.agent.llm_response": (
"{}"
),
"gcp.vertex.agent.tool_call_args": (
"{}"
),
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.tool_response": (
"{}"
),
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.system": "gemini",
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
},
logs=[
LogDigest(
event_name=GEN_AI_CHOICE_EVENT,
body={
"content": "<elided>",
"index": 0,
"finish_reason": "STOP",
},
attributes={
"gen_ai.system": "gemini"
},
),
LogDigest(
event_name=GEN_AI_SYSTEM_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={
"gen_ai.system": "gemini"
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={
"gen_ai.system": "gemini"
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={
"gen_ai.system": "gemini"
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={
"gen_ai.system": "gemini"
},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": (
PRESENT
),
},
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Stable semconv, OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true
# ---------------------------------------------------------------------------
EXPECTED_STABLE_CAPTURE_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.system": "gemini",
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
},
logs=[
LogDigest(
event_name=GEN_AI_CHOICE_EVENT,
body={
"content": {
"parts": [{
"function_call": {
"args": TOOL_ARGS,
"name": TOOL_NAME,
}
}],
"role": "model",
},
"index": 0,
"finish_reason": "STOP",
},
attributes={
"gen_ai.system": "gemini"
},
),
LogDigest(
event_name=GEN_AI_SYSTEM_MESSAGE_EVENT,
body={
"content": (
_NODE_SYSTEM_INSTRUCTION
)
},
attributes={
"gen_ai.system": "gemini"
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [{
"text": (
_AGENT_USER_INPUT
)
}],
"role": "user",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "some_user",
},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": (
"execute_tool"
),
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": (
"FunctionTool"
),
"gcp.vertex.agent.llm_request": (
"{}"
),
"gcp.vertex.agent.llm_response": (
"{}"
),
"gcp.vertex.agent.tool_call_args": (
"{}"
),
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.tool_response": (
"{}"
),
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.system": "gemini",
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
},
logs=[
LogDigest(
event_name=GEN_AI_CHOICE_EVENT,
body={
"content": {
"parts": [
{"text": FINAL_TEXT}
],
"role": "model",
},
"index": 0,
"finish_reason": "STOP",
},
attributes={
"gen_ai.system": "gemini"
},
),
LogDigest(
event_name=GEN_AI_SYSTEM_MESSAGE_EVENT,
body={
"content": (
_NODE_SYSTEM_INSTRUCTION
)
},
attributes={
"gen_ai.system": "gemini"
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [{
"function_call": {
"args": TOOL_ARGS,
"name": TOOL_NAME,
}
}],
"role": "model",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "some_user",
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [{
"function_response": {
"name": TOOL_NAME,
"response": {
"result": (
TOOL_RESULT
)
},
}
}],
"role": "user",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "some_user",
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [{
"text": (
_AGENT_USER_INPUT
)
}],
"role": "user",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "some_user",
},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": (
PRESENT
),
},
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Experimental semconv,
# OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=no_content
# ---------------------------------------------------------------------------
EXPECTED_EXPERIMENTAL_NO_CONTENT_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [{
"name": TOOL_NAME,
"description": TOOL_DESCRIPTION,
"type": "function",
}],
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": (
PRESENT
),
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [{
"name": TOOL_NAME,
"description": (
TOOL_DESCRIPTION
),
"type": "function",
}],
},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": (
"execute_tool"
),
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": (
"FunctionTool"
),
"gcp.vertex.agent.llm_request": (
"{}"
),
"gcp.vertex.agent.llm_response": (
"{}"
),
"gcp.vertex.agent.tool_call_args": (
"{}"
),
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.tool_response": (
"{}"
),
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [{
"name": TOOL_NAME,
"description": TOOL_DESCRIPTION,
"type": "function",
}],
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": (
PRESENT
),
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [{
"name": TOOL_NAME,
"description": (
TOOL_DESCRIPTION
),
"type": "function",
}],
},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": (
PRESENT
),
},
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Op-detail building blocks for the experimental cases.
# ---------------------------------------------------------------------------
_TOOL_DEFINITION_FULL = {
"name": TOOL_NAME,
"description": TOOL_DESCRIPTION,
"parameters": {
"properties": {"arg1": {"title": "Arg1", "type": "string"}},
"required": ["arg1"],
"title": f"{TOOL_NAME}Params",
"type": "object",
},
"type": "function",
}
_TOOL_DEFINITION_NO_CONTENT = {
"name": TOOL_NAME,
"description": TOOL_DESCRIPTION,
"type": "function",
}
_SYSTEM_INSTRUCTIONS = [{"content": _NODE_SYSTEM_INSTRUCTION, "type": "text"}]
_TURN_1_INPUT_MESSAGES = [{
"role": "user",
"parts": [{"content": _AGENT_USER_INPUT, "type": "text"}],
}]
_TURN_1_OUTPUT_MESSAGES = [{
"role": "assistant",
"parts": [{
"id": f"{TOOL_NAME}_0",
"name": TOOL_NAME,
"arguments": TOOL_ARGS,
"type": "tool_call",
}],
"finish_reason": "stop",
}]
_TURN_2_INPUT_MESSAGES = [
{
"role": "user",
"parts": [{"content": _AGENT_USER_INPUT, "type": "text"}],
},
{
"role": "assistant",
"parts": [{
"id": f"{TOOL_NAME}_0",
"name": TOOL_NAME,
"arguments": TOOL_ARGS,
"type": "tool_call",
}],
},
{
"role": "user",
"parts": [{
"id": f"{TOOL_NAME}_0",
"response": {"result": TOOL_RESULT},
"type": "tool_call_response",
}],
},
]
_TURN_2_OUTPUT_MESSAGES = [{
"role": "assistant",
"parts": [{"content": FINAL_TEXT, "type": "text"}],
"finish_reason": "stop",
}]
# ---------------------------------------------------------------------------
# Experimental semconv,
# OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=span_only
# ---------------------------------------------------------------------------
EXPECTED_EXPERIMENTAL_SPAN_ONLY_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_1_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_1_OUTPUT_MESSAGES
),
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": (
PRESENT
),
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_NO_CONTENT
],
},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": (
"execute_tool"
),
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": (
"FunctionTool"
),
"gcp.vertex.agent.llm_request": (
"{}"
),
"gcp.vertex.agent.llm_response": (
"{}"
),
"gcp.vertex.agent.tool_call_args": (
"{}"
),
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.tool_response": (
"{}"
),
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_2_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_2_OUTPUT_MESSAGES
),
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": (
PRESENT
),
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_NO_CONTENT
],
},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": (
PRESENT
),
},
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Experimental semconv,
# OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=event_only
# ---------------------------------------------------------------------------
EXPECTED_EXPERIMENTAL_EVENT_ONLY_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_NO_CONTENT
],
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": (
PRESENT
),
"user.id": "some_user",
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_1_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_1_OUTPUT_MESSAGES
),
},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": (
"execute_tool"
),
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": (
"FunctionTool"
),
"gcp.vertex.agent.llm_request": (
"{}"
),
"gcp.vertex.agent.llm_response": (
"{}"
),
"gcp.vertex.agent.tool_call_args": (
"{}"
),
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.tool_response": (
"{}"
),
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_NO_CONTENT
],
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": (
PRESENT
),
"user.id": "some_user",
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_2_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_2_OUTPUT_MESSAGES
),
},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": (
PRESENT
),
},
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Experimental semconv,
# OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=span_and_event
# ---------------------------------------------------------------------------
EXPECTED_EXPERIMENTAL_SPAN_AND_EVENT_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_1_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_1_OUTPUT_MESSAGES
),
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": (
PRESENT
),
"user.id": "some_user",
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_1_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_1_OUTPUT_MESSAGES
),
},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": (
"execute_tool"
),
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": (
"FunctionTool"
),
"gcp.vertex.agent.llm_request": (
"{}"
),
"gcp.vertex.agent.llm_response": (
"{}"
),
"gcp.vertex.agent.tool_call_args": (
"{}"
),
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.tool_response": (
"{}"
),
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": (
"generate_content"
),
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_2_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_2_OUTPUT_MESSAGES
),
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": (
PRESENT
),
"user.id": "some_user",
"gcp.vertex.agent.event_id": (
PRESENT
),
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_2_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_2_OUTPUT_MESSAGES
),
},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": (
PRESENT
),
},
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Schema v2 expected shapes.
# ---------------------------------------------------------------------------
EXPECTED_STABLE_NO_CAPTURE_V2 = SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.system": "gemini",
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
},
logs=[
LogDigest(
event_name=GEN_AI_CHOICE_EVENT,
body={
"content": "<elided>",
"index": 0,
"finish_reason": "STOP",
},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_SYSTEM_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={"gen_ai.system": "gemini"},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": "execute_tool",
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": "FunctionTool",
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gcp.vertex.agent.tool_call_args": "{}",
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.tool_response": "{}",
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.system": "gemini",
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
},
logs=[
LogDigest(
event_name=GEN_AI_CHOICE_EVENT,
body={
"content": "<elided>",
"index": 0,
"finish_reason": "STOP",
},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_SYSTEM_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={"content": "<elided>"},
attributes={"gen_ai.system": "gemini"},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": PRESENT,
},
),
],
),
],
)
EXPECTED_STABLE_CAPTURE_V2 = SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.system": "gemini",
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
},
logs=[
LogDigest(
event_name=GEN_AI_CHOICE_EVENT,
body={
"content": {
"parts": [{
"function_call": {
"args": TOOL_ARGS,
"name": TOOL_NAME,
}
}],
"role": "model",
},
"index": 0,
"finish_reason": "STOP",
},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_SYSTEM_MESSAGE_EVENT,
body={"content": _NODE_SYSTEM_INSTRUCTION},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [
{"text": _AGENT_USER_INPUT}
],
"role": "user",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "some_user",
},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": "execute_tool",
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": "FunctionTool",
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gcp.vertex.agent.tool_call_args": "{}",
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.tool_response": "{}",
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.system": "gemini",
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
},
logs=[
LogDigest(
event_name=GEN_AI_CHOICE_EVENT,
body={
"content": {
"parts": [{"text": FINAL_TEXT}],
"role": "model",
},
"index": 0,
"finish_reason": "STOP",
},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_SYSTEM_MESSAGE_EVENT,
body={"content": _NODE_SYSTEM_INSTRUCTION},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [{
"function_call": {
"args": TOOL_ARGS,
"name": TOOL_NAME,
}
}],
"role": "model",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "some_user",
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [{
"function_response": {
"name": TOOL_NAME,
"response": {
"result": TOOL_RESULT
},
}
}],
"role": "user",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "some_user",
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [
{"text": _AGENT_USER_INPUT}
],
"role": "user",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "some_user",
},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": PRESENT,
},
),
],
),
],
)
EXPECTED_EXPERIMENTAL_NO_CONTENT_V2 = SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
"gen_ai.tool.definitions": [{
"name": TOOL_NAME,
"description": TOOL_DESCRIPTION,
"type": "function",
}],
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [{
"name": TOOL_NAME,
"description": TOOL_DESCRIPTION,
"type": "function",
}],
},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": "execute_tool",
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": "FunctionTool",
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gcp.vertex.agent.tool_call_args": "{}",
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.tool_response": "{}",
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
"gen_ai.tool.definitions": [{
"name": TOOL_NAME,
"description": TOOL_DESCRIPTION,
"type": "function",
}],
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [{
"name": TOOL_NAME,
"description": TOOL_DESCRIPTION,
"type": "function",
}],
},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": PRESENT,
},
),
],
),
],
)
EXPECTED_EXPERIMENTAL_SPAN_ONLY_V2 = SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
"gen_ai.input.messages": _TURN_1_INPUT_MESSAGES,
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_1_OUTPUT_MESSAGES
),
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_NO_CONTENT
],
},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": "execute_tool",
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": "FunctionTool",
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gcp.vertex.agent.tool_call_args": "{}",
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.tool_response": "{}",
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
"gen_ai.input.messages": _TURN_2_INPUT_MESSAGES,
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_2_OUTPUT_MESSAGES
),
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_NO_CONTENT
],
},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": PRESENT,
},
),
],
),
],
)
EXPECTED_EXPERIMENTAL_EVENT_ONLY_V2 = SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_NO_CONTENT
],
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"user.id": "some_user",
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_1_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_1_OUTPUT_MESSAGES
),
},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": "execute_tool",
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": "FunctionTool",
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gcp.vertex.agent.tool_call_args": "{}",
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.tool_response": "{}",
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_NO_CONTENT
],
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"user.id": "some_user",
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_2_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_2_OUTPUT_MESSAGES
),
},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": PRESENT,
},
),
],
),
],
)
EXPECTED_EXPERIMENTAL_SPAN_AND_EVENT_V2 = SpanDigest(
name=f"invoke_workflow {WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_agent {AGENT_NAME}",
attributes={
"gen_ai.operation.name": "invoke_agent",
"gen_ai.agent.description": AGENT_DESCRIPTION,
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
"gen_ai.input.messages": _TURN_1_INPUT_MESSAGES,
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_1_OUTPUT_MESSAGES
),
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"user.id": "some_user",
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_1_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_1_OUTPUT_MESSAGES
),
},
),
],
children=[
SpanDigest(
name=f"execute_tool {TOOL_NAME}",
attributes={
"gen_ai.operation.name": "execute_tool",
"gen_ai.tool.description": (
TOOL_DESCRIPTION
),
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": "FunctionTool",
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gcp.vertex.agent.tool_call_args": "{}",
"gen_ai.tool.call.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.tool_response": "{}",
},
),
],
),
],
),
SpanDigest(
name="call_llm",
attributes={
"gen_ai.system": "gcp.vertex.agent",
"gen_ai.request.model": "mock",
"gcp.vertex.agent.invocation_id": PRESENT,
"gcp.vertex.agent.session_id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.llm_request": "{}",
"gcp.vertex.agent.llm_response": "{}",
"gen_ai.response.finish_reasons": ["stop"],
},
children=[
SpanDigest(
name="generate_content mock",
attributes={
"gen_ai.operation.name": "generate_content",
"gen_ai.request.model": "mock",
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": PRESENT,
"gen_ai.response.finish_reasons": ["stop"],
"gen_ai.input.messages": _TURN_2_INPUT_MESSAGES,
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_2_OUTPUT_MESSAGES
),
},
logs=[
LogDigest(
event_name=(
GEN_AI_COMPLETION_DETAILS_EVENT
),
body=None,
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
"user.id": "some_user",
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.response.finish_reasons": [
"stop"
],
"gen_ai.input.messages": (
_TURN_2_INPUT_MESSAGES
),
"gen_ai.system_instructions": (
_SYSTEM_INSTRUCTIONS
),
"gen_ai.tool.definitions": [
_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_TURN_2_OUTPUT_MESSAGES
),
},
),
],
),
],
),
],
),
SpanDigest(
name=f"invoke_workflow {NESTED_WORKFLOW_NAME}",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name=f"invoke_node {NODE_NAME}",
attributes={
"gen_ai.operation.name": "invoke_node",
"gen_ai.conversation.id": PRESENT,
"gcp.vertex.agent.associated_event_ids": PRESENT,
},
),
],
),
],
)
# Expected metric points, grouped by metric name.
EXPECTED_NODE_METRICS_V1: dict[str, frozenset[MetricPoint]] = {
"gen_ai.invoke_agent.duration": frozenset({
MetricPoint(
attributes={"gen_ai.agent.name": AGENT_NAME},
value=NON_DETERMINISTIC,
),
}),
"gen_ai.execute_tool.duration": frozenset({
MetricPoint(
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": "FunctionTool",
},
value=NON_DETERMINISTIC,
),
}),
"gen_ai.client.operation.duration": frozenset({
MetricPoint(
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.operation.name": "generate_content",
"gen_ai.provider.name": "gemini",
"gen_ai.request.model": "mock",
"gen_ai.response.model": "mock",
},
value=NON_DETERMINISTIC,
),
}),
"gen_ai.invoke_workflow.duration": frozenset({
MetricPoint(
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
},
value=NON_DETERMINISTIC,
),
# Nested workflow carries the `gen_ai.workflow.nested` dimension; the
# root workflow above omits it.
MetricPoint(
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
},
value=NON_DETERMINISTIC,
),
}),
"gen_ai.invoke_agent.inference_calls": frozenset({
MetricPoint(attributes={"gen_ai.agent.name": AGENT_NAME}, value=2),
}),
"gen_ai.invoke_agent.tool_calls": frozenset({
MetricPoint(attributes={"gen_ai.agent.name": AGENT_NAME}, value=1),
}),
}
EXPECTED_NODE_METRICS_V2: dict[str, frozenset[MetricPoint]] = {
"gen_ai.invoke_agent.duration": frozenset({
MetricPoint(
attributes={"gen_ai.agent.name": AGENT_NAME},
value=NON_DETERMINISTIC,
),
}),
"gen_ai.execute_tool.duration": frozenset({
MetricPoint(
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.tool.name": TOOL_NAME,
"gen_ai.tool.type": "FunctionTool",
},
value=NON_DETERMINISTIC,
),
}),
"gen_ai.client.operation.duration": frozenset({
MetricPoint(
attributes={
"gen_ai.agent.name": AGENT_NAME,
"gen_ai.operation.name": "generate_content",
"gen_ai.provider.name": "gemini",
"gen_ai.request.model": "mock",
"gen_ai.response.model": "mock",
},
value=NON_DETERMINISTIC,
),
}),
"gen_ai.invoke_workflow.duration": frozenset({
MetricPoint(
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": WORKFLOW_NAME,
},
value=NON_DETERMINISTIC,
),
# Nested workflow carries the `gen_ai.workflow.nested` dimension; the
# root workflow above omits it.
MetricPoint(
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": NESTED_WORKFLOW_NAME,
"gen_ai.workflow.nested": True,
},
value=NON_DETERMINISTIC,
),
}),
"gen_ai.invoke_agent.inference_calls": frozenset({
MetricPoint(attributes={"gen_ai.agent.name": AGENT_NAME}, value=2),
}),
"gen_ai.invoke_agent.tool_calls": frozenset({
MetricPoint(attributes={"gen_ai.agent.name": AGENT_NAME}, value=1),
}),
}
# ---------------------------------------------------------------------------
# Parametrization list.
# ---------------------------------------------------------------------------
ALL_NODE_CASES: list[FunctionalTestCase] = [
FunctionalTestCase(
test_id="stable-no-capture-schema-v1",
semconv_opt_in=None,
capture_content="false",
schema_version=1,
expected=TelemetryDigest(
root_span=EXPECTED_STABLE_NO_CAPTURE_V1,
metric_points=EXPECTED_NODE_METRICS_V1,
),
),
FunctionalTestCase(
test_id="stable-no-capture-schema-v2",
semconv_opt_in=None,
capture_content="false",
schema_version=2,
expected=TelemetryDigest(
root_span=EXPECTED_STABLE_NO_CAPTURE_V2,
metric_points=EXPECTED_NODE_METRICS_V2,
),
),
FunctionalTestCase(
test_id="stable-capture-schema-v1",
semconv_opt_in=None,
capture_content="true",
schema_version=1,
expected=TelemetryDigest(
root_span=EXPECTED_STABLE_CAPTURE_V1,
metric_points=EXPECTED_NODE_METRICS_V1,
),
),
FunctionalTestCase(
test_id="stable-capture-schema-v2",
semconv_opt_in=None,
capture_content="true",
schema_version=2,
expected=TelemetryDigest(
root_span=EXPECTED_STABLE_CAPTURE_V2,
metric_points=EXPECTED_NODE_METRICS_V2,
),
),
FunctionalTestCase(
test_id="experimental-no-content-schema-v1",
semconv_opt_in=EXPERIMENTAL_OPT_IN,
capture_content="no_content",
schema_version=1,
expected=TelemetryDigest(
root_span=EXPECTED_EXPERIMENTAL_NO_CONTENT_V1,
metric_points=EXPECTED_NODE_METRICS_V1,
),
),
FunctionalTestCase(
test_id="experimental-no-content-schema-v2",
semconv_opt_in=EXPERIMENTAL_OPT_IN,
capture_content="no_content",
schema_version=2,
expected=TelemetryDigest(
root_span=EXPECTED_EXPERIMENTAL_NO_CONTENT_V2,
metric_points=EXPECTED_NODE_METRICS_V2,
),
),
FunctionalTestCase(
test_id="experimental-span-only-schema-v1",
semconv_opt_in=EXPERIMENTAL_OPT_IN,
capture_content="span_only",
schema_version=1,
expected=TelemetryDigest(
root_span=EXPECTED_EXPERIMENTAL_SPAN_ONLY_V1,
metric_points=EXPECTED_NODE_METRICS_V1,
),
),
FunctionalTestCase(
test_id="experimental-span-only-schema-v2",
semconv_opt_in=EXPERIMENTAL_OPT_IN,
capture_content="span_only",
schema_version=2,
expected=TelemetryDigest(
root_span=EXPECTED_EXPERIMENTAL_SPAN_ONLY_V2,
metric_points=EXPECTED_NODE_METRICS_V2,
),
),
FunctionalTestCase(
test_id="experimental-event-only-schema-v1",
semconv_opt_in=EXPERIMENTAL_OPT_IN,
capture_content="event_only",
schema_version=1,
expected=TelemetryDigest(
root_span=EXPECTED_EXPERIMENTAL_EVENT_ONLY_V1,
metric_points=EXPECTED_NODE_METRICS_V1,
),
),
FunctionalTestCase(
test_id="experimental-event-only-schema-v2",
semconv_opt_in=EXPERIMENTAL_OPT_IN,
capture_content="event_only",
schema_version=2,
expected=TelemetryDigest(
root_span=EXPECTED_EXPERIMENTAL_EVENT_ONLY_V2,
metric_points=EXPECTED_NODE_METRICS_V2,
),
),
FunctionalTestCase(
test_id="experimental-span-and-event-schema-v1",
semconv_opt_in=EXPERIMENTAL_OPT_IN,
capture_content="span_and_event",
schema_version=1,
expected=TelemetryDigest(
root_span=EXPECTED_EXPERIMENTAL_SPAN_AND_EVENT_V1,
metric_points=EXPECTED_NODE_METRICS_V1,
),
),
FunctionalTestCase(
test_id="experimental-span-and-event-schema-v2",
semconv_opt_in=EXPERIMENTAL_OPT_IN,
capture_content="span_and_event",
schema_version=2,
expected=TelemetryDigest(
root_span=EXPECTED_EXPERIMENTAL_SPAN_AND_EVENT_V2,
metric_points=EXPECTED_NODE_METRICS_V2,
),
),
]
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