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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 non-node functional tests.
Each ``EXPECTED_*`` is a complete ``SpanDigest`` tree (with per-span
``LogDigest`` lists nested in) describing what telemetry the canonical
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 EXPERIMENTAL_OPT_IN
from .functional_test_helpers import FINAL_TEXT
from .functional_test_helpers import FULL_SYSTEM_INSTRUCTION
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 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
# ---------------------------------------------------------------------------
# Stable semconv, OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=false
# ---------------------------------------------------------------------------
EXPECTED_STABLE_NO_CAPTURE_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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="execute_tool some_tool",
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"},
),
],
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Stable semconv, OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true
# ---------------------------------------------------------------------------
EXPECTED_STABLE_CAPTURE_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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": FULL_SYSTEM_INSTRUCTION},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [{"text": USER_PROMPT}],
"role": "user",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "test_user",
},
),
],
children=[
SpanDigest(
name="execute_tool some_tool",
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": FULL_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": "test_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": "test_user",
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [{"text": USER_PROMPT}],
"role": "user",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "test_user",
},
),
],
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Experimental semconv,
# OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=no_content
# ---------------------------------------------------------------------------
# `no_content` is not one of the recognized capturing modes, so it falls into
# the "no content" branch on both the span and the log: function-tool params
# are stripped to None, no input/output messages, no system instructions.
EXPECTED_EXPERIMENTAL_NO_CONTENT_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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="execute_tool some_tool",
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",
}],
},
),
],
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Experimental semconv,
# OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=span_only
# ---------------------------------------------------------------------------
# Span gets full op-details (input/output messages, system instructions, full
# tool definitions). Log carries the no-content view.
# Tool definition with full parameters (only on spans/logs that get content).
_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": FULL_SYSTEM_INSTRUCTION, "type": "text"}]
_TURN_1_INPUT_MESSAGES = [{
"role": "user",
"parts": [{"content": USER_PROMPT, "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": USER_PROMPT, "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",
}]
EXPECTED_EXPERIMENTAL_SPAN_ONLY_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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="execute_tool some_tool",
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
],
},
),
],
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Experimental semconv,
# OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=event_only
# ---------------------------------------------------------------------------
# Span gets the no-content view (only tool definitions, with params=None).
# Log gets the full op-details (input/output messages, system instructions,
# full tool definitions).
EXPECTED_EXPERIMENTAL_EVENT_ONLY_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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": "test_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="execute_tool some_tool",
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": "test_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
),
},
),
],
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Experimental semconv,
# OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=span_and_event
# ---------------------------------------------------------------------------
# Both span and log get the full op-details.
EXPECTED_EXPERIMENTAL_SPAN_AND_EVENT_V1 = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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": "test_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="execute_tool some_tool",
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": "test_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
),
},
),
],
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# MCP-integration single-turn shape (experimental semconv only).
#
# Used by ``test_functional.py``'s MCP integration test. The scenario is
# a single-turn agent (``MockModel`` returns text immediately) whose only
# tool source is an ``McpToolset`` whose underlying session exposes one
# ``mcp_echo`` tool. ``McpToolset`` calls ``list_tools()`` once per agent
# invocation and materializes the result into a ``FunctionDeclaration``;
# the experimental semconv builder reads that declaration straight from
# ``llm_request.config.tools`` without ever talking to the MCP server
# itself.
#
# Only the experimental path needs a dedicated shape: stable semconv
# doesn't emit ``gen_ai.tool.definitions`` at all, so the MCP integration
# would be indistinguishable from any other tool-bearing agent under
# stable semconv.
#
# In ``EXPECTED_EXPERIMENTAL_SPAN_AND_EVENT_WITH_MCP``, the MCP-resolved
# ``mcp_echo`` definition surfaces in both ``gen_ai.tool.definitions``
# (span attribute) and the same key on the completion-details log
# record. The ``parameters`` block uses standard JSON Schema vocabulary
# (``object``, ``string``) because ``McpTool._get_declaration`` passes
# the MCP ``inputSchema`` through ``parameters_json_schema`` when the
# ``JSON_SCHEMA_FOR_FUNC_DECL`` feature is enabled.
# ---------------------------------------------------------------------------
_MCP_TOOL_NAME = "mcp_echo"
_MCP_TOOL_DESCRIPTION = "Echoes back its input."
_MCP_TOOL_DEFINITION_FULL = {
"name": _MCP_TOOL_NAME,
"description": _MCP_TOOL_DESCRIPTION,
"parameters": {
"properties": {"text": {"type": "string"}},
"required": ["text"],
"type": "object",
},
"type": "function",
}
_MCP_TURN_INPUT_MESSAGES = [{
"role": "user",
"parts": [{"content": USER_PROMPT, "type": "text"}],
}]
_MCP_TURN_OUTPUT_MESSAGES = [{
"role": "assistant",
"parts": [{"content": FINAL_TEXT, "type": "text"}],
# ``MockModel`` does not populate ``finish_reason``; it surfaces here as
# the empty string from ``_to_finish_reason(None)``.
"finish_reason": "",
}]
EXPECTED_EXPERIMENTAL_SPAN_AND_EVENT_WITH_MCP = SpanDigest(
name="invocation",
attributes={},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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": "{}",
},
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.input.messages": (
_MCP_TURN_INPUT_MESSAGES
),
"gen_ai.system_instructions": [{
"content": FULL_SYSTEM_INSTRUCTION,
"type": "text",
}],
"gen_ai.tool.definitions": [
_MCP_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_MCP_TURN_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": "test_user",
"gcp.vertex.agent.event_id": PRESENT,
"gcp.vertex.agent.invocation_id": (
PRESENT
),
"gen_ai.input.messages": (
_MCP_TURN_INPUT_MESSAGES
),
"gen_ai.system_instructions": [{
"content": FULL_SYSTEM_INSTRUCTION,
"type": "text",
}],
"gen_ai.tool.definitions": [
_MCP_TOOL_DEFINITION_FULL
],
"gen_ai.output.messages": (
_MCP_TURN_OUTPUT_MESSAGES
),
},
),
],
),
],
),
],
),
],
)
# ---------------------------------------------------------------------------
# Schema v2 expected shapes.
# ---------------------------------------------------------------------------
EXPECTED_STABLE_NO_CAPTURE_V2 = SpanDigest(
name="invoke_workflow some_root_agent",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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="execute_tool some_tool",
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"},
),
],
),
],
),
],
),
],
)
EXPECTED_STABLE_CAPTURE_V2 = SpanDigest(
name="invoke_workflow some_root_agent",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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": FULL_SYSTEM_INSTRUCTION},
attributes={"gen_ai.system": "gemini"},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [{"text": USER_PROMPT}],
"role": "user",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "test_user",
},
),
],
children=[
SpanDigest(
name="execute_tool some_tool",
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": FULL_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": "test_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": "test_user",
},
),
LogDigest(
event_name=GEN_AI_USER_MESSAGE_EVENT,
body={
"content": {
"parts": [{"text": USER_PROMPT}],
"role": "user",
}
},
attributes={
"gen_ai.system": "gemini",
"user.id": "test_user",
},
),
],
),
],
),
],
),
],
)
EXPECTED_EXPERIMENTAL_NO_CONTENT_V2 = SpanDigest(
name="invoke_workflow some_root_agent",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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="execute_tool some_tool",
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",
}],
},
),
],
),
],
),
],
),
],
)
EXPECTED_EXPERIMENTAL_SPAN_ONLY_V2 = SpanDigest(
name="invoke_workflow some_root_agent",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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="execute_tool some_tool",
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
],
},
),
],
),
],
),
],
),
],
)
EXPECTED_EXPERIMENTAL_EVENT_ONLY_V2 = SpanDigest(
name="invoke_workflow some_root_agent",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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": "test_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="execute_tool some_tool",
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": "test_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
),
},
),
],
),
],
),
],
),
],
)
EXPECTED_EXPERIMENTAL_SPAN_AND_EVENT_V2 = SpanDigest(
name="invoke_workflow some_root_agent",
attributes={
"gen_ai.operation.name": "invoke_workflow",
"gen_ai.workflow.name": AGENT_NAME,
"gen_ai.conversation.id": PRESENT,
},
children=[
SpanDigest(
name="invoke_agent some_root_agent",
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": "test_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="execute_tool some_tool",
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": "test_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
),
},
),
],
),
],
),
],
),
],
)
# Expected metric points, grouped by metric name.
EXPECTED_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_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_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": AGENT_NAME,
},
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_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_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_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_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_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_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_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_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_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_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_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_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_METRICS_V2,
),
),
]
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