Class ConversationsClient (2.27.0)

Service for managing Conversations.

Returns the transport used by the client instance.

Instantiates the conversations client.

Releases underlying transport's resources.

Returns a fully-qualified agent string.

Returns a fully-qualified answer_record string.

Starts asynchronous cancellation on a long-running operation.

The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Returns a fully-qualified billing_account string.

Returns a fully-qualified folder string.

Returns a fully-qualified location string.

Returns a fully-qualified organization string.

Returns a fully-qualified project string.

Completes the specified conversation. Finished conversations are purged from the database after 30 days.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2

def sample_complete_conversation():
    # Create a client
    client = dialogflow_v2.ConversationsClient()

    # Initialize request argument(s)
    request = dialogflow_v2.CompleteConversationRequest(
        name="name_value",
    )

    # Make the request
    response = client.complete_conversation(request=request)

    # Handle the response
    print(response)

Returns a fully-qualified conversation_model string.

Returns a fully-qualified conversation string.

Returns a fully-qualified conversation_profile string.

Creates a new conversation. Conversations are auto-completed after 24 hours.

Conversation Lifecycle: There are two stages during a conversation: Automated Agent Stage and Assist Stage.

For Automated Agent Stage, there will be a dialogflow agent responding to user queries.

For Assist Stage, there's no dialogflow agent responding to user queries. But we will provide suggestions which are generated from conversation.

If xref_Conversation.conversation_profile is configured for a dialogflow agent, conversation will start from Automated Agent Stage, otherwise, it will start from Assist Stage. And during Automated Agent Stage, once an xref_Intent with xref_Intent.live_agent_handoff is triggered, conversation will transfer to Assist Stage.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2

def sample_create_conversation():
    # Create a client
    client = dialogflow_v2.ConversationsClient()

    # Initialize request argument(s)
    conversation = dialogflow_v2.Conversation()
    conversation.conversation_profile = "conversation_profile_value"

    request = dialogflow_v2.CreateConversationRequest(
        parent="parent_value",
        conversation=conversation,
    )

    # Make the request
    response = client.create_conversation(request=request)

    # Handle the response
    print(response)

Returns a fully-qualified cx_security_settings string.

Returns a fully-qualified document string.

Creates an instance of this client using the provided credentials file.

Creates an instance of this client using the provided credentials info.

Creates an instance of this client using the provided credentials file.

Generates and returns a summary for a conversation that does not have a resource created for it.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2

def sample_generate_stateless_summary():
    # Create a client
    client = dialogflow_v2.ConversationsClient()

    # Initialize request argument(s)
    stateless_conversation = dialogflow_v2.MinimalConversation()
    stateless_conversation.messages.content = "content_value"
    stateless_conversation.parent = "parent_value"

    conversation_profile = dialogflow_v2.ConversationProfile()
    conversation_profile.display_name = "display_name_value"

    request = dialogflow_v2.GenerateStatelessSummaryRequest(
        stateless_conversation=stateless_conversation,
        conversation_profile=conversation_profile,
    )

    # Make the request
    response = client.generate_stateless_summary(request=request)

    # Handle the response
    print(response)

Retrieves the specific conversation.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2

def sample_get_conversation():
    # Create a client
    client = dialogflow_v2.ConversationsClient()

    # Initialize request argument(s)
    request = dialogflow_v2.GetConversationRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_conversation(request=request)

    # Handle the response
    print(response)

Gets information about a location.

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variable is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Gets the latest state of a long-running operation.

Returns a fully-qualified knowledge_base string.

Returns the list of all conversations in the specified project.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2

def sample_list_conversations():
    # Create a client
    client = dialogflow_v2.ConversationsClient()

    # Initialize request argument(s)
    request = dialogflow_v2.ListConversationsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_conversations(request=request)

    # Handle the response
    for response in page_result:
        print(response)

Lists information about the supported locations for this service.

Lists messages that belong to a given conversation. messages are ordered by create_time in descending order. To fetch updates without duplication, send request with filter create_time_epoch_microseconds > [first item's create_time of previous request] and empty page_token.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2

def sample_list_messages():
    # Create a client
    client = dialogflow_v2.ConversationsClient()

    # Initialize request argument(s)
    request = dialogflow_v2.ListMessagesRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_messages(request=request)

    # Handle the response
    for response in page_result:
        print(response)

Lists operations that match the specified filter in the request.

Returns a fully-qualified message string.

Parses a agent path into its component segments.

Parses a answer_record path into its component segments.

Parse a billing_account path into its component segments.

Parse a folder path into its component segments.

Parse a location path into its component segments.

Parse a organization path into its component segments.

Parse a project path into its component segments.

Parses a conversation_model path into its component segments.

Parses a conversation path into its component segments.

Parses a conversation_profile path into its component segments.

Parses a cx_security_settings path into its component segments.

Parses a document path into its component segments.

Parses a knowledge_base path into its component segments.

Parses a message path into its component segments.

Get answers for the given query based on knowledge documents.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2

def sample_search_knowledge():
    # Create a client
    client = dialogflow_v2.ConversationsClient()

    # Initialize request argument(s)
    query = dialogflow_v2.TextInput()
    query.text = "text_value"
    query.language_code = "language_code_value"

    request = dialogflow_v2.SearchKnowledgeRequest(
        query=query,
        conversation_profile="conversation_profile_value",
    )

    # Make the request
    response = client.search_knowledge(request=request)

    # Handle the response
    print(response)

Suggests summary for a conversation based on specific historical messages. The range of the messages to be used for summary can be specified in the request.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2

def sample_suggest_conversation_summary():
    # Create a client
    client = dialogflow_v2.ConversationsClient()

    # Initialize request argument(s)
    request = dialogflow_v2.SuggestConversationSummaryRequest(
        conversation="conversation_value",
    )

    # Make the request
    response = client.suggest_conversation_summary(request=request)

    # Handle the response
    print(response)