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import functools
import pytest
from devtools_testutils import AzureRecordedTestCase, EnvironmentVariableLoader, recorded_by_proxy
from azure.ai.language.conversations import ConversationAnalysisClient
from azure.ai.language.conversations.models import (
AnalyzeConversationActionResult,
ConversationActionContent,
ConversationAnalysisInput,
TextConversationItem,
StringIndexType,
ConversationLanguageUnderstandingInput,
OrchestrationPrediction,
QuestionAnsweringTargetIntentResult,
ConversationActionResult,
)
from typing import cast
from azure.core.credentials import AzureKeyCredential
ConversationsPreparer = functools.partial(
EnvironmentVariableLoader,
"conversations",
conversations_endpoint="https://Sanitized.cognitiveservices.azure.com/",
conversations_key="fake_key",
)
class TestConversations(AzureRecordedTestCase):
# Start with any helper functions you might need, for example a client creation method:
def create_client(self, endpoint, key):
credential = AzureKeyCredential(key)
client = ConversationAnalysisClient(endpoint, credential)
return client
...
class TestConversationsCase(TestConversations):
@ConversationsPreparer()
@recorded_by_proxy
def test_orchestration_prediction(self, conversations_endpoint, conversations_key):
client = self.create_client(conversations_endpoint, conversations_key)
project_name = "TestWorkflow"
deployment_name = "production"
# Build request using strongly-typed models
data = ConversationLanguageUnderstandingInput(
conversation_input=ConversationAnalysisInput(
conversation_item=TextConversationItem(
id="1",
participant_id="participant1",
text="How are you?",
)
),
action_content=ConversationActionContent(
project_name=project_name,
deployment_name=deployment_name,
string_index_type=StringIndexType.UTF16_CODE_UNIT,
),
)
response: AnalyzeConversationActionResult = client.analyze_conversation(data)
conversation_result = cast(ConversationActionResult, response)
prediction = conversation_result.result.prediction
assert isinstance(prediction, OrchestrationPrediction)
assert prediction.top_intent is not None, "top_intent missing in orchestration prediction"
responding_project_name = cast(str, prediction.top_intent)
print(f"Top intent: {responding_project_name}")
target_intent_result = prediction.intents[responding_project_name]
assert isinstance(target_intent_result, QuestionAnsweringTargetIntentResult)
qa = target_intent_result.result
for ans in qa.answers: # type: ignore
print(ans.answer or "")
# Final assertions like in C#
assert responding_project_name == "ChitChat-QnA"
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