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# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
import os
import azure.ai.inference as sdk
from azure.ai.inference.tracing import AIInferenceInstrumentor
from model_inference_test_base import (
ModelClientTestBase,
ServicePreparerChatCompletions,
)
from azure.core.settings import settings
from devtools_testutils.aio import recorded_by_proxy_async
from memory_trace_exporter import MemoryTraceExporter
from gen_ai_trace_verifier import GenAiTraceVerifier
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
CONTENT_TRACING_ENV_VARIABLE = "AZURE_TRACING_GEN_AI_CONTENT_RECORDING_ENABLED"
content_tracing_initial_value = os.getenv(CONTENT_TRACING_ENV_VARIABLE)
# The test class name needs to start with "Test" to get collected by pytest
class TestClientTracingAsync(ModelClientTestBase):
@classmethod
def teardown_class(cls):
if content_tracing_initial_value is not None:
os.environ[CONTENT_TRACING_ENV_VARIABLE] = content_tracing_initial_value
# **********************************************************************************
#
# TRACING TESTS - CHAT COMPLETIONS
#
# **********************************************************************************
def setup_memory_trace_exporter(self) -> MemoryTraceExporter:
# Setup Azure Core settings to use OpenTelemetry tracing
settings.tracing_implementation = "OpenTelemetry"
trace.set_tracer_provider(TracerProvider())
_ = trace.get_tracer(__name__)
memoryExporter = MemoryTraceExporter()
span_processor = SimpleSpanProcessor(memoryExporter)
trace.get_tracer_provider().add_span_processor(span_processor)
return span_processor, memoryExporter
def modify_env_var(self, name, new_value):
current_value = os.getenv(name)
os.environ[name] = new_value
return current_value
@ServicePreparerChatCompletions()
@recorded_by_proxy_async
async def test_chat_completion_async_tracing_content_recording_disabled(self, **kwargs):
# Make sure code is not instrumented due to a previous test exception
try:
AIInferenceInstrumentor().uninstrument()
except RuntimeError as e:
pass
self.modify_env_var(CONTENT_TRACING_ENV_VARIABLE, "False")
client = self._create_async_chat_client(**kwargs)
model = kwargs.pop("azure_ai_chat_model").lower()
processor, exporter = self.setup_memory_trace_exporter()
AIInferenceInstrumentor().instrument()
_ = await client.complete(
messages=[
sdk.models.SystemMessage(content="You are a helpful assistant."),
sdk.models.UserMessage(content="What is the capital of France?"),
],
)
processor.force_flush()
spans = exporter.get_spans_by_name_starts_with("chat ")
if len(spans) == 0:
spans = exporter.get_spans_by_name("chat")
assert len(spans) == 1
span = spans[0]
expected_attributes = [
("gen_ai.operation.name", "chat"),
("gen_ai.system", "az.ai.inference"),
("gen_ai.request.model", "chat"),
("server.address", ""),
("gen_ai.response.id", ""),
("gen_ai.response.model", model),
("gen_ai.usage.input_tokens", "+"),
("gen_ai.usage.output_tokens", "+"),
("gen_ai.response.finish_reasons", ("stop",)),
]
attributes_match = GenAiTraceVerifier().check_span_attributes(span, expected_attributes)
assert attributes_match == True
expected_events = [
{
"name": "gen_ai.choice",
"attributes": {
"gen_ai.system": "az.ai.inference",
"gen_ai.event.content": '{"finish_reason": "stop", "index": 0}',
},
}
]
events_match = GenAiTraceVerifier().check_span_events(span, expected_events)
assert events_match == True
AIInferenceInstrumentor().uninstrument()
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