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# pylint: disable=line-too-long,useless-suppression
import functools
import pytest
from devtools_testutils import AzureRecordedTestCase, EnvironmentVariableLoader
from devtools_testutils.aio import recorded_by_proxy_async
from azure.core.credentials import AzureKeyCredential
from azure.ai.language.conversations.authoring.aio import ConversationAuthoringClient
ConversationsPreparer = functools.partial(
EnvironmentVariableLoader,
"authoring",
authoring_endpoint="https://Sanitized.cognitiveservices.azure.com/",
authoring_key="fake_key",
)
class TestConversationsAsync(AzureRecordedTestCase):
async def create_client(self, endpoint: str, key: str) -> ConversationAuthoringClient:
return ConversationAuthoringClient(endpoint, AzureKeyCredential(key))
class TestConversationsGetModelEvaluationSummaryAsync(TestConversationsAsync):
@ConversationsPreparer()
@recorded_by_proxy_async
@pytest.mark.asyncio
async def test_get_model_evaluation_summary_async(self, authoring_endpoint, authoring_key):
client = await self.create_client(authoring_endpoint, authoring_key)
try:
project_name = "EmailApp"
trained_model_label = "Model1"
# Get trained-model scoped client and fetch the evaluation summary
project_client = client.get_project_client(project_name)
eval_summary = await project_client.trained_model.get_model_evaluation_summary(trained_model_label)
# Basic assertion
assert eval_summary is not None
# ----- Entities evaluation (micro/macro) -----
entities_eval = getattr(eval_summary, "entities_evaluation", None)
if entities_eval:
print(
f"Entities - Micro F1: {getattr(entities_eval, 'micro_f1', None)}, Micro Precision: {getattr(entities_eval, 'micro_precision', None)}, Micro Recall: {getattr(entities_eval, 'micro_recall', None)}"
)
print(
f"Entities - Macro F1: {getattr(entities_eval, 'macro_f1', None)}, Macro Precision: {getattr(entities_eval, 'macro_precision', None)}, Macro Recall: {getattr(entities_eval, 'macro_recall', None)}"
)
ent_map = getattr(entities_eval, "entities", {}) or {}
for name, summary in ent_map.items():
print(
f"Entity '{name}': F1 = {getattr(summary, 'f1', None)}, Precision = {getattr(summary, 'precision', None)}, Recall = {getattr(summary, 'recall', None)}"
)
print(
f" True Positives: {getattr(summary, 'true_positive_count', None)}, True Negatives: {getattr(summary, 'true_negative_count', None)}"
)
print(
f" False Positives: {getattr(summary, 'false_positive_count', None)}, False Negatives: {getattr(summary, 'false_negative_count', None)}"
)
# ----- Intents evaluation (micro/macro) -----
intents_eval = getattr(eval_summary, "intents_evaluation", None)
if intents_eval:
print(
f"Intents - Micro F1: {getattr(intents_eval, 'micro_f1', None)}, Micro Precision: {getattr(intents_eval, 'micro_precision', None)}, Micro Recall: {getattr(intents_eval, 'micro_recall', None)}"
)
print(
f"Intents - Macro F1: {getattr(intents_eval, 'macro_f1', None)}, Macro Precision: {getattr(intents_eval, 'macro_precision', None)}, Macro Recall: {getattr(intents_eval, 'macro_recall', None)}"
)
intent_map = getattr(intents_eval, "intents", {}) or {}
for name, summary in intent_map.items():
print(
f"Intent '{name}': F1 = {getattr(summary, 'f1', None)}, Precision = {getattr(summary, 'precision', None)}, Recall = {getattr(summary, 'recall', None)}"
)
print(
f" True Positives: {getattr(summary, 'true_positive_count', None)}, True Negatives: {getattr(summary, 'true_negative_count', None)}"
)
print(
f" False Positives: {getattr(summary, 'false_positive_count', None)}, False Negatives: {getattr(summary, 'false_negative_count', None)}"
)
finally:
await client.close()
|
