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# pylint: disable=line-too-long,useless-suppression
import functools
import pytest
from devtools_testutils import AzureRecordedTestCase, EnvironmentVariableLoader, recorded_by_proxy
from azure.core.credentials import AzureKeyCredential
from azure.ai.language.conversations.authoring import ConversationAuthoringClient
ConversationsPreparer = functools.partial(
EnvironmentVariableLoader,
"authoring",
authoring_endpoint="https://Sanitized.cognitiveservices.azure.com/",
authoring_key="fake_key",
)
class TestConversations(AzureRecordedTestCase):
def create_client(self, endpoint, key):
return ConversationAuthoringClient(endpoint, AzureKeyCredential(key))
class TestConversationsGetModelEvaluationSummarySync(TestConversations):
@ConversationsPreparer()
@recorded_by_proxy
def test_get_model_evaluation_summary(self, authoring_endpoint, authoring_key):
authoring_client = self.create_client(authoring_endpoint, authoring_key)
project_name = "EmailApp"
trained_model_label = "Model1"
# Get trained-model scoped client and fetch the evaluation summary
project_client = authoring_client.get_project_client(project_name)
eval_summary = project_client.trained_model.get_model_evaluation_summary(trained_model_label)
# Basic assertion the call returned something shaped like a summary
assert eval_summary is not None
# ----- Entities evaluation (micro/macro) -----
entities_summary = eval_summary.entities_evaluation
if entities_summary is not None:
print(
f"Entities - Micro F1: {entities_summary.micro_f1}, "
f"Micro Precision: {entities_summary.micro_precision}, "
f"Micro Recall: {entities_summary.micro_recall}"
)
print(
f"Entities - Macro F1: {entities_summary.macro_f1}, "
f"Macro Precision: {entities_summary.macro_precision}, "
f"Macro Recall: {entities_summary.macro_recall}"
)
# Per-entity details
ent_map = entities_summary.entities or {}
for name, summary in ent_map.items():
print(f"Entity '{name}': F1 = {summary.f1}, Precision = {summary.precision}, Recall = {summary.recall}")
print(
f" True Positives: {summary.true_positive_count}, "
f"True Negatives: {summary.true_negative_count}"
)
print(
f" False Positives: {summary.false_positive_count}, "
f"False Negatives: {summary.false_negative_count}"
)
# ----- Intents evaluation (micro/macro) -----
intents_summary = eval_summary.intents_evaluation
if intents_summary is not None:
print(
f"Intents - Micro F1: {intents_summary.micro_f1}, "
f"Micro Precision: {intents_summary.micro_precision}, "
f"Micro Recall: {intents_summary.micro_recall}"
)
print(
f"Intents - Macro F1: {intents_summary.macro_f1}, "
f"Macro Precision: {intents_summary.macro_precision}, "
f"Macro Recall: {intents_summary.macro_recall}"
)
# Per-intent details
intent_map = intents_summary.intents or {}
for name, summary in intent_map.items():
print(f"Intent '{name}': F1 = {summary.f1}, Precision = {summary.precision}, Recall = {summary.recall}")
print(
f" True Positives: {summary.true_positive_count}, "
f"True Negatives: {summary.true_negative_count}"
)
print(
f" False Positives: {summary.false_positive_count}, "
f"False Negatives: {summary.false_negative_count}"
)
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