def test_create_conversation_profile(capsys):
# Check the conversation profile does not yet exists.
conversation_profile_management.list_conversation_profiles(PROJECT_ID)
out, _ = capsys.readouterr()
assert 'Display Name: {}'.format(
CONVERSATION_PROFILE_DISPLAY_NAME) not in out
# Create a conversation profile.
conversation_profile_management.create_conversation_profile_article_faq(
project_id=PROJECT_ID, display_name=CONVERSATION_PROFILE_DISPLAY_NAME,
article_suggestion_knowledge_base_id='abc')
out, _ = capsys.readouterr()
assert 'Display Name: {}'.format(
CONVERSATION_PROFILE_DISPLAY_NAME) in out
conversation_profile_id = out.split('conversationProfiles/')[1].rstrip()
# List conversation profiles.
conversation_profile_management.list_conversation_profiles(PROJECT_ID)
out, _ = capsys.readouterr()
assert 'Display Name: {}'.format(
CONVERSATION_PROFILE_DISPLAY_NAME) in out
# Get the conversation profile.
conversation_profile_management.get_conversation_profile(
PROJECT_ID, conversation_profile_id)
out, _ = capsys.readouterr()
assert 'Display Name: {}'.format(CONVERSATION_PROFILE_DISPLAY_NAME) in out
# Delete the conversation profile.
conversation_profile_management.delete_conversation_profile(
PROJECT_ID, conversation_profile_id)
# Verify the converstion profile is deleted.
conversation_profile_management.list_conversation_profiles(PROJECT_ID)
out, _ = capsys.readouterr()
assert 'Display Name: {}'.format(
CONVERSATION_PROFILE_DISPLAY_NAME) not in out
def test_smart_reply(capsys):
"""Test smart reply feature.
"""
# Create conversation profile.
conversation_profile_management.create_conversation_profile_smart_reply(
project_id=PROJECT_ID,
display_name=CONVERSATION_PROFILE_DISPLAY_NAME,
smart_reply_allowlist_name=SMART_REPLY_ALLOWLIST,
smart_reply_model_name=SMART_REPLY_MODEL,
)
out, _ = capsys.readouterr()
assert "Display Name: {}".format(CONVERSATION_PROFILE_DISPLAY_NAME) in out
conversation_profile_id = out.split("conversationProfiles/")[1].rstrip()
# Create conversation.
conversation_management.create_conversation(
project_id=PROJECT_ID, conversation_profile_id=conversation_profile_id
)
out, _ = capsys.readouterr()
conversation_id = out.split("conversations/")[1].rstrip()
# Create end user participant.
participant_management.create_participant(
project_id=PROJECT_ID, conversation_id=conversation_id, role="END_USER"
)
out, _ = capsys.readouterr()
end_user_id = out.split("participants/")[1].rstrip()
# Create human agent participant.
participant_management.create_participant(
project_id=PROJECT_ID, conversation_id=conversation_id, role="HUMAN_AGENT"
)
out, _ = capsys.readouterr()
human_agent_id = out.split("participants/")[1].rstrip()
# AnalyzeContent
participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=human_agent_id,
text="Hi, how are you?",
)
out, _ = capsys.readouterr()
assert "What would you like to know?" in out
response = participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=end_user_id,
text="I am doing well, just want to check",
)
out, _ = capsys.readouterr()
assert "Sounds good." in out
# Update AnswerRecord.
answer_record_id = (
response.human_agent_suggestion_results[0]
.suggest_smart_replies_response.smart_reply_answers[0]
.answer_record.split("answerRecords/")[1]
.rstrip()
)
answer_record_management.update_answer_record(
project_id=PROJECT_ID, answer_record_id=answer_record_id, is_clicked=True
)
out, _ = capsys.readouterr()
assert "Clicked: True" in out
# Complete conversation.
conversation_management.complete_conversation(
project_id=PROJECT_ID, conversation_id=conversation_id
)
# Delete conversation profile.
conversation_profile_management.delete_conversation_profile(
project_id=PROJECT_ID, conversation_profile_id=conversation_profile_id
)
def test_analyze_content_text(capsys):
"""Test analyze content api with text only messages.
"""
# Create knowledge base.
knowledge_base_management.create_knowledge_base(
PROJECT_ID, KNOWLEDGE_BASE_DISPLAY_NAME)
out, _ = capsys.readouterr()
knowledge_base_id = out.split('knowledgeBases/')[1].rstrip()
# Get the knowledge base
knowledge_base_management.get_knowledge_base(PROJECT_ID, knowledge_base_id)
out, _ = capsys.readouterr()
assert 'Display Name: {}'.format(KNOWLEDGE_BASE_DISPLAY_NAME) in out
# Create documents. Note that you should get read permission of bucket gs://ruogu/parsed_5_24/7157212.html
# via Pantheon for service account (google application credential account) from here:
# https://pantheon.corp.google.com/storage/browser/ruogu/parsed_5_24/?project=agent-assistant-demo
document_management.create_document(PROJECT_ID, knowledge_base_id,
DOCUMENT_DISPLAY_NAME, 'text/html',
'ARTICLE_SUGGESTION',
'gs://ruogu/parsed_5_24/7157212.html')
out, _ = capsys.readouterr()
document_id = out.split('documents/')[1].split(' - MIME Type:')[0].rstrip()
# Get the Document
document_management.get_document(PROJECT_ID, knowledge_base_id,
document_id)
out, _ = capsys.readouterr()
assert 'Display Name: {}'.format(DOCUMENT_DISPLAY_NAME) in out
# Create conversation profile.
conversation_profile_management.create_conversation_profile_article_faq(
project_id=PROJECT_ID,
display_name=CONVERSATION_PROFILE_DISPLAY_NAME,
article_suggestion_knowledge_base_id=knowledge_base_id)
out, _ = capsys.readouterr()
assert 'Display Name: {}'.format(CONVERSATION_PROFILE_DISPLAY_NAME) in out
conversation_profile_id = out.split('conversationProfiles/')[1].rstrip()
# Create conversation.
conversation_management.create_conversation(
project_id=PROJECT_ID, conversation_profile_id=conversation_profile_id)
out, _ = capsys.readouterr()
conversation_id = out.split('conversations/')[1].rstrip()
# Create end user participant.
participant_management.create_participant(project_id=PROJECT_ID,
conversation_id=conversation_id,
role='END_USER')
out, _ = capsys.readouterr()
end_user_id = out.split('participants/')[1].rstrip()
# Create human agent participant.
participant_management.create_participant(project_id=PROJECT_ID,
conversation_id=conversation_id,
role='HUMAN_AGENT')
out, _ = capsys.readouterr()
human_agent_id = out.split('participants/')[1].rstrip()
# AnalyzeContent
participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=human_agent_id,
text='Hi, how are you?')
out, _ = capsys.readouterr()
participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=end_user_id,
text='Hi, I am doing well, how about you?')
out, _ = capsys.readouterr()
participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=human_agent_id,
text='Great. How can I help you?')
out, _ = capsys.readouterr()
participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=end_user_id,
text='So I ordered something, but I do not like it.')
out, _ = capsys.readouterr()
participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=end_user_id,
text='Thinking if I can cancel that order')
suggestion_out, _ = capsys.readouterr()
# Currently suggestion_out won't contain the suggestion we want since it
# takes time for document to be ready to serve.
# assert 'Cancel an order' in suggestion_out
# Complete conversation.
conversation_management.complete_conversation(
project_id=PROJECT_ID, conversation_id=conversation_id)
# Delete conversation profile.
conversation_profile_management.delete_conversation_profile(
project_id=PROJECT_ID, conversation_profile_id=conversation_profile_id)
# Delete document.
document_management.delete_document(PROJECT_ID, knowledge_base_id,
document_id)
# Delete the Knowledge Base.
knowledge_base_management.delete_knowledge_base(PROJECT_ID,
knowledge_base_id)
def test_analyze_content_text(capsys):
"""Test analyze content api with text only messages.
"""
# Create knowledge base.
knowledge_base_management.create_knowledge_base(
PROJECT_ID, KNOWLEDGE_BASE_DISPLAY_NAME)
out, _ = capsys.readouterr()
knowledge_base_id = out.split("knowledgeBases/")[1].rstrip()
# Get the knowledge base
knowledge_base_management.get_knowledge_base(PROJECT_ID, knowledge_base_id)
out, _ = capsys.readouterr()
assert "Display Name: {}".format(KNOWLEDGE_BASE_DISPLAY_NAME) in out
# Create documents. Note that you should get read permission of bucket gs://cloud-samples-data/dialogflow/participant_test.html
# via Pantheon for service account (google application credential account) from here:
# https://support.google.com/googleshopping/answer/9116497
document_management.create_document(
PROJECT_ID,
knowledge_base_id,
DOCUMENT_DISPLAY_NAME,
"text/html",
"ARTICLE_SUGGESTION",
"gs://cloud-samples-data/dialogflow/participant_test.html",
)
out, _ = capsys.readouterr()
document_id = out.split("documents/")[1].split(" - MIME Type:")[0].rstrip()
# Get the Document
document_management.get_document(PROJECT_ID, knowledge_base_id,
document_id)
out, _ = capsys.readouterr()
assert "Display Name: {}".format(DOCUMENT_DISPLAY_NAME) in out
# Create conversation profile.
conversation_profile_management.create_conversation_profile_article_faq(
project_id=PROJECT_ID,
display_name=CONVERSATION_PROFILE_DISPLAY_NAME,
article_suggestion_knowledge_base_id=knowledge_base_id,
)
out, _ = capsys.readouterr()
assert "Display Name: {}".format(CONVERSATION_PROFILE_DISPLAY_NAME) in out
conversation_profile_id = out.split("conversationProfiles/")[1].rstrip()
# Create conversation.
conversation_management.create_conversation(
project_id=PROJECT_ID, conversation_profile_id=conversation_profile_id)
out, _ = capsys.readouterr()
conversation_id = out.split("conversations/")[1].rstrip()
# Create end user participant.
participant_management.create_participant(project_id=PROJECT_ID,
conversation_id=conversation_id,
role="END_USER")
out, _ = capsys.readouterr()
end_user_id = out.split("participants/")[1].rstrip()
# Create human agent participant.
participant_management.create_participant(project_id=PROJECT_ID,
conversation_id=conversation_id,
role="HUMAN_AGENT")
out, _ = capsys.readouterr()
human_agent_id = out.split("participants/")[1].rstrip()
# AnalyzeContent
participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=human_agent_id,
text="Hi, how are you?",
)
out, _ = capsys.readouterr()
participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=end_user_id,
text="Hi, I am doing well, how about you?",
)
out, _ = capsys.readouterr()
participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=human_agent_id,
text="Great. How can I help you?",
)
out, _ = capsys.readouterr()
participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=end_user_id,
text="So I ordered something, but I do not like it.",
)
out, _ = capsys.readouterr()
participant_management.analyze_content_text(
project_id=PROJECT_ID,
conversation_id=conversation_id,
participant_id=end_user_id,
text="Thinking if I can cancel that order",
)
suggestion_out, _ = capsys.readouterr()
# Currently suggestion_out won't contain the suggestion we want since it
# takes time for document to be ready to serve.
# assert 'Cancel an order' in suggestion_out
# Complete conversation.
conversation_management.complete_conversation(
project_id=PROJECT_ID, conversation_id=conversation_id)
# Delete conversation profile.
conversation_profile_management.delete_conversation_profile(
project_id=PROJECT_ID, conversation_profile_id=conversation_profile_id)
# Delete document.
document_management.delete_document(PROJECT_ID, knowledge_base_id,
document_id)
# Delete the Knowledge Base.
knowledge_base_management.delete_knowledge_base(PROJECT_ID,
knowledge_base_id)