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docs(samples): add Agent Assist code samples (#267)
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‎dialogflow/answer_record_management.py

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#!/usr/bin/env python
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# Copyright 2021 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Dialogflow API Python sample showing how to manage AnswerRecord.
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"""
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from google.cloud import dialogflow_v2beta1 as dialogflow
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# [START dialogflow_update_answer_record]
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def update_answer_record(project_id, answer_record_id, is_clicked):
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"""Update the answer record.
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Args:
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project_id: The GCP project linked with the conversation profile.
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answer_record_id: The answer record id returned along with the
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suggestion.
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is_clicked: whether the answer record is clicked."""
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client = dialogflow.AnswerRecordsClient()
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answer_record_path = client.answer_record_path(project_id,
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answer_record_id)
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response = client.update_answer_record(
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answer_record={
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'name': answer_record_path,
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'answer_feedback': {
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'clicked': is_clicked
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}
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},
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update_mask={'paths': ['answer_feedback']})
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print('AnswerRecord Name: {}'.format(response.name))
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print('Clicked: {}'.format(response.answer_feedback.clicked))
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return response
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# [END dialogflow_update_answer_record]

‎dialogflow/answer_record_management_test.py

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# Copyright 2021 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import answer_record_management
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import conversation_management
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import conversation_profile_management
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import participant_management
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PROJECT_ID = os.getenv('GOOGLE_CLOUD_PROJECT')
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SMART_REPLY_MODEL = os.getenv('SMART_REPLY_MODEL')
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SMART_REPLY_ALLOWLIST = os.getenv('SMART_REPLY_ALLOWLIST')
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CONVERSATION_PROFILE_DISPLAY_NAME = 'sample code profile for smart reply'
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def test_smart_reply(capsys):
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"""Test smart reply feature.
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"""
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# Create conversation profile.
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conversation_profile_management.create_conversation_profile_smart_reply(
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project_id=PROJECT_ID,
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display_name=CONVERSATION_PROFILE_DISPLAY_NAME,
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smart_reply_allowlist_name=SMART_REPLY_ALLOWLIST,
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smart_reply_model_name=SMART_REPLY_MODEL)
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out, _ = capsys.readouterr()
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assert 'Display Name: {}'.format(CONVERSATION_PROFILE_DISPLAY_NAME) in out
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conversation_profile_id = out.split('conversationProfiles/')[1].rstrip()
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# Create conversation.
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conversation_management.create_conversation(
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project_id=PROJECT_ID, conversation_profile_id=conversation_profile_id)
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out, _ = capsys.readouterr()
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conversation_id = out.split('conversations/')[1].rstrip()
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# Create end user participant.
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participant_management.create_participant(project_id=PROJECT_ID,
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conversation_id=conversation_id,
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role='END_USER')
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out, _ = capsys.readouterr()
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end_user_id = out.split('participants/')[1].rstrip()
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# Create human agent participant.
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participant_management.create_participant(project_id=PROJECT_ID,
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conversation_id=conversation_id,
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role='HUMAN_AGENT')
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out, _ = capsys.readouterr()
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human_agent_id = out.split('participants/')[1].rstrip()
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# AnalyzeContent
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participant_management.analyze_content_text(
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project_id=PROJECT_ID,
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conversation_id=conversation_id,
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participant_id=human_agent_id,
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text='Hi, how are you?')
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out, _ = capsys.readouterr()
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assert 'What would you like to know?' in out
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response = participant_management.analyze_content_text(
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project_id=PROJECT_ID,
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conversation_id=conversation_id,
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participant_id=end_user_id,
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text='I am doing well, just want to check')
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out, _ = capsys.readouterr()
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assert 'Sounds good.' in out
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# Update AnswerRecord.
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answer_record_id = response.human_agent_suggestion_results[
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0].suggest_smart_replies_response.smart_reply_answers[
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0].answer_record.split('answerRecords/')[1].rstrip()
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answer_record_management.update_answer_record(
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project_id=PROJECT_ID,
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answer_record_id=answer_record_id,
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is_clicked=True)
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out, _ = capsys.readouterr()
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assert 'Clicked: True' in out
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# Complete conversation.
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conversation_management.complete_conversation(
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project_id=PROJECT_ID, conversation_id=conversation_id)
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# Delete conversation profile.
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conversation_profile_management.delete_conversation_profile(
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project_id=PROJECT_ID, conversation_profile_id=conversation_profile_id)

‎dialogflow/conversation_management.py

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#!/usr/bin/env python
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# Copyright 2021 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Dialogflow API Python sample showing how to manage Conversations.
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"""
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from google.cloud import dialogflow_v2beta1 as dialogflow
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# [START dialogflow_create_conversation]
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def create_conversation(project_id, conversation_profile_id):
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"""Creates a conversation with given values
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Args:
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project_id: The GCP project linked with the conversation.
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conversation_profile_id: The conversation profile id used to create
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conversation."""
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client = dialogflow.ConversationsClient()
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conversation_profile_client = dialogflow.ConversationProfilesClient()
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project_path = client.common_project_path(project_id)
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conversation_profile_path = (
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conversation_profile_client.conversation_profile_path(
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project_id, conversation_profile_id))
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conversation = {'conversation_profile': conversation_profile_path}
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response = client.create_conversation(parent=project_path,
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conversation=conversation)
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print('Life Cycle State: {}'.format(response.lifecycle_state))
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print('Conversation Profile Name: {}'.format(
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response.conversation_profile))
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print('Name: {}'.format(response.name))
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return response
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# [END dialogflow_create_conversation]
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# [START dialogflow_get_conversation]
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def get_conversation(project_id, conversation_id):
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"""Gets a specific conversation profile.
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Args:
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project_id: The GCP project linked with the conversation.
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conversation_id: Id of the conversation."""
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client = dialogflow.ConversationsClient()
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conversation_path = client.conversation_path(project_id, conversation_id)
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response = client.get_conversation(name=conversation_path)
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print('Life Cycle State: {}'.format(response.lifecycle_state))
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print('Conversation Profile Name: {}'.format(
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response.conversation_profile))
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print('Name: {}'.format(response.name))
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return response
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# [END dialogflow_get_conversation]
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# [START dialogflow_complete_conversation]
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def complete_conversation(project_id, conversation_id):
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"""Completes the specified conversation. Finished conversations are purged from the database after 30 days.
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Args:
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project_id: The GCP project linked with the conversation.
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conversation_id: Id of the conversation."""
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client = dialogflow.ConversationsClient()
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conversation_path = client.conversation_path(project_id, conversation_id)
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conversation = client.complete_conversation(name=conversation_path)
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print('Completed Conversation.')
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print('Life Cycle State: {}'.format(conversation.lifecycle_state))
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print('Conversation Profile Name: {}'.format(
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conversation.conversation_profile))
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print('Name: {}'.format(conversation.name))
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return conversation
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# [END dialogflow_complete_conversation]

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