def sample_streaming_analyze_content():
# Create a client
client = dialogflow_v2beta1.ParticipantsClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.StreamingAnalyzeContentRequest(
input_audio=b'input_audio_blob',
participant="participant_value",
)
# This method expects an iterator which contains
# 'dialogflow_v2beta1.StreamingAnalyzeContentRequest' objects
# Here we create a generator that yields a single `request` for
# demonstrative purposes.
requests = [request]
def request_generator():
for request in requests:
yield request
# Make the request
stream = client.streaming_analyze_content(requests=request_generator())
# Handle the response
for response in stream:
print(response)
def analyze_content_text(project_id, conversation_id, participant_id, text):
"""Analyze text message content from a participant.
Args:
project_id: The GCP project linked with the conversation profile.
conversation_id: Id of the conversation.
participant_id: Id of the participant.
text: the text message that participant typed."""
client = dialogflow.ParticipantsClient()
participant_path = client.participant_path(project_id, conversation_id,
participant_id)
text_input = {"text": text, "language_code": "en-US"}
response = client.analyze_content(participant=participant_path,
text_input=text_input)
print("AnalyzeContent Response:")
print("Reply Text: {}".format(response.reply_text))
for suggestion_result in response.human_agent_suggestion_results:
if suggestion_result.error is not None:
print("Error: {}".format(suggestion_result.error.message))
if suggestion_result.suggest_articles_response:
for answer in suggestion_result.suggest_articles_response.article_answers:
print("Article Suggestion Answer: {}".format(answer.title))
print("Answer Record: {}".format(answer.answer_record))
if suggestion_result.suggest_faq_answers_response:
for answer in suggestion_result.suggest_faq_answers_response.faq_answers:
print("Faq Answer: {}".format(answer.answer))
print("Answer Record: {}".format(answer.answer_record))
if suggestion_result.suggest_smart_replies_response:
for (
answer
) in suggestion_result.suggest_smart_replies_response.smart_reply_answers:
print("Smart Reply: {}".format(answer.reply))
print("Answer Record: {}".format(answer.answer_record))
for suggestion_result in response.end_user_suggestion_results:
if suggestion_result.error:
print("Error: {}".format(suggestion_result.error.message))
if suggestion_result.suggest_articles_response:
for answer in suggestion_result.suggest_articles_response.article_answers:
print("Article Suggestion Answer: {}".format(answer.title))
print("Answer Record: {}".format(answer.answer_record))
if suggestion_result.suggest_faq_answers_response:
for answer in suggestion_result.suggest_faq_answers_response.faq_answers:
print("Faq Answer: {}".format(answer.answer))
print("Answer Record: {}".format(answer.answer_record))
if suggestion_result.suggest_smart_replies_response:
for (
answer
) in suggestion_result.suggest_smart_replies_response.smart_reply_answers:
print("Smart Reply: {}".format(answer.reply))
print("Answer Record: {}".format(answer.answer_record))
return response
def sample_update_participant():
# Create a client
client = dialogflow_v2beta1.ParticipantsClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.UpdateParticipantRequest()
# Make the request
response = client.update_participant(request=request)
# Handle the response
print(response)
def sample_get_participant():
# Create a client
client = dialogflow_v2beta1.ParticipantsClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.GetParticipantRequest(name="name_value", )
# Make the request
response = client.get_participant(request=request)
# Handle the response
print(response)
def sample_compile_suggestion():
# Create a client
client = dialogflow_v2beta1.ParticipantsClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.CompileSuggestionRequest()
# Make the request
response = client.compile_suggestion(request=request)
# Handle the response
print(response)
def sample_suggest_faq_answers():
# Create a client
client = dialogflow_v2beta1.ParticipantsClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.SuggestFaqAnswersRequest(
parent="parent_value", )
# Make the request
response = client.suggest_faq_answers(request=request)
# Handle the response
print(response)
def sample_list_suggestions():
# Create a client
client = dialogflow_v2beta1.ParticipantsClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.ListSuggestionsRequest()
# Make the request
page_result = client.list_suggestions(request=request)
# Handle the response
for response in page_result:
print(response)
def sample_analyze_content():
# Create a client
client = dialogflow_v2beta1.ParticipantsClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.AnalyzeContentRequest(
participant="participant_value", )
# Make the request
response = client.analyze_content(request=request)
# Handle the response
print(response)
def create_participant(project_id, conversation_id, role):
"""Creates a participant in a given conversation.
Args:
project_id: The GCP project linked with the conversation profile.
conversation_id: Id of the conversation.
participant: participant to be created."""
client = dialogflow.ParticipantsClient()
conversation_path = dialogflow.ConversationsClient.conversation_path(
project_id, conversation_id)
if role in ROLES:
response = client.create_participant(parent=conversation_path,
participant={'role': role})
print('Participant Created.')
print('Role: {}'.format(response.role))
print('Name: {}'.format(response.name))
return response
