Central instance to access all Dialogflow related resource activities
Hierarchical advanced settings for agent/flow/page/fulfillment/parameter. Settings exposed at lower level overrides the settings exposed at higher level. Overriding occurs at the sub-setting level. For example, the playback_interruption_settings at fulfillment level only overrides the playback_interruption_settings at the agent level, leaving other settings at the agent level unchanged. DTMF settings does not override each other. DTMF settings set at different levels define DTMF detections running in parallel. Hierarchy: Agent->Flow->Page->Fulfillment/Parameter.
Define behaviors for DTMF (dual tone multi frequency).
Define behaviors on logging.
Agents are best described as Natural Language Understanding (NLU) modules that transform user requests into actionable data. You can include agents in your app, product, or service to determine user intent and respond to the user in a natural way. After you create an agent, you can add Intents, Entity Types, Flows, Fulfillments, Webhooks, TransitionRouteGroups and so on to manage the conversation flows.
Settings for answer feedback collection.
Settings for Gen App Builder.
Settings for connecting to Git repository for an agent.
Settings of integration with GitHub.
The response message for Agents.GetAgentValidationResult.
Stores information about feedback provided by users about a response.
Stores extra information about why users provided thumbs down rating.
Represents the natural speech audio to be processed.
Configuration of the barge-in behavior. Barge-in instructs the API to return a detected utterance at a proper time while the client is playing back the response audio from a previous request. When the client sees the utterance, it should stop the playback and immediately get ready for receiving the responses for the current request. The barge-in handling requires the client to start streaming audio input as soon as it starts playing back the audio from the previous response. The playback is modeled into two phases: * No barge-in phase: which goes first and during which speech detection should not be carried out. * Barge-in phase: which follows the no barge-in phase and during which the API starts speech detection and may inform the client that an utterance has been detected. Note that no-speech event is not expected in this phase. The client provides this configuration in terms of the durations of those two phases. The durations are measured in terms of the audio length from the the start of the input audio. No-speech event is a response with END_OF_UTTERANCE without any transcript following up.
The request message for TestCases.BatchDeleteTestCases.
The request message for TestCases.BatchRunTestCases.
Boost specification to boost certain documents. A copy of google.cloud.discoveryengine.v1main.BoostSpec, field documentation is available at https://cloud.google.com/generative-ai-app-builder/docs/reference/rest/v1alpha/BoostSpec
Boost applies to documents which match a condition.
Boost specifications for data stores.
The response message for TestCases.CalculateCoverage.
Changelogs represents a change made to a given agent.
The request message for Versions.CompareVersions.
The response message for Versions.CompareVersions.
Represents a result from running a test case in an agent environment.
One interaction between a human and virtual agent. The human provides some input and the virtual agent provides a response.
The input from the human user.
The output from the virtual agent.
A data store connection. It represents a data store in Discovery Engine and the type of the contents it contains.
The request message for Environments.DeployFlow.
Represents a deployment in an environment. A deployment happens when a flow version configured to be active in the environment. You can configure running pre-deployment steps, e.g. running validation test cases, experiment auto-rollout, etc.
Result of the deployment.
The request to detect user’s intent.
The message returned from the DetectIntent method.
Represents the input for dtmf event.
Entities are extracted from user input and represent parameters that are meaningful to your application. For example, a date range, a proper name such as a geographic location or landmark, and so on. Entities represent actionable data for your application. When you define an entity, you can also include synonyms that all map to that entity. For example, “soft drink”, “soda”, “pop”, and so on. There are three types of entities: *
System - entities that are defined by the Dialogflow API for common data types such as date, time, currency, and so on. A system entity is represented by the
EntityType type. *
Custom - entities that are defined by you that represent actionable data that is meaningful to your application. For example, you could define a
pizza.sauce entity for red or white pizza sauce, a
pizza.cheese entity for the different types of cheese on a pizza, a
pizza.topping entity for different toppings, and so on. A custom entity is represented by the
EntityType type. *
User - entities that are built for an individual user such as favorites, preferences, playlists, and so on. A user entity is represented by the SessionEntityType type. For more information about entity types, see the
Dialogflow documentation.
An entity entry for an associated entity type.
An excluded entity phrase that should not be matched.
Represents an environment for an agent. You can create multiple versions of your agent and publish them to separate environments. When you edit an agent, you are editing the draft agent. At any point, you can save the draft agent as an agent version, which is an immutable snapshot of your agent. When you save the draft agent, it is published to the default environment. When you create agent versions, you can publish them to custom environments. You can create a variety of custom environments for testing, development, production, etc.
The configuration for continuous tests.
Configuration for the version.
Configuration for webhooks.
An event handler specifies an event that can be handled during a session. When the specified event happens, the following actions are taken in order: * If there is a trigger_fulfillment associated with the event, it will be called. * If there is a target_page associated with the event, the session will transition into the specified page. * If there is a target_flow associated with the event, the session will transition into the specified flow.
Represents the event to trigger.
Represents an experiment in an environment.
Definition of the experiment.
The inference result which includes an objective metric to optimize and the confidence interval.
A confidence interval is a range of possible values for the experiment objective you are trying to measure.
Metric and corresponding confidence intervals.
Version variant and associated metrics.
The request message for Agents.ExportAgent.
Settings for exporting to a git branch.
The request message for EntityTypes.ExportEntityTypes.
The request message for Flows.ExportFlow.
The request message for Intents.ExportIntents.
The request message for TestCases.ExportTestCases.
Filter specifications for data stores.
Flows represents the conversation flows when you build your chatbot agent. A flow consists of many pages connected by the transition routes. Conversations always start with the built-in Start Flow (with an all-0 ID). Transition routes can direct the conversation session from the current flow (parent flow) to another flow (sub flow). When the sub flow is finished, Dialogflow will bring the session back to the parent flow, where the sub flow is started. Usually, when a transition route is followed by a matched intent, the intent will be “consumed”. This means the intent won’t activate more transition routes. However, when the followed transition route moves the conversation session into a different flow, the matched intent can be carried over and to be consumed in the target flow.
The flow import strategy used for resource conflict resolution associated with an ImportFlowRequest.
The response message for Flows.GetFlowValidationResult.
A form is a data model that groups related parameters that can be collected from the user. The process in which the agent prompts the user and collects parameter values from the user is called form filling. A form can be added to a page. When form filling is done, the filled parameters will be written to the session.
Represents a form parameter.
Configuration for how the filling of a parameter should be handled.
Request of FulfillIntent
Response of FulfillIntent
A fulfillment can do one or more of the following actions at the same time: * Generate rich message responses. * Set parameter values. * Call the webhook. Fulfillments can be called at various stages in the Page or Form lifecycle. For example, when a DetectIntentRequest drives a session to enter a new page, the page’s entry fulfillment can add a static response to the QueryResult in the returning DetectIntentResponse, call the webhook (for example, to load user data from a database), or both.
A list of cascading if-else conditions. Cases are mutually exclusive. The first one with a matching condition is selected, all the rest ignored.
Each case has a Boolean condition. When it is evaluated to be True, the corresponding messages will be selected and evaluated recursively.
The list of messages or conditional cases to activate for this case.
Setting a parameter value.
Google Cloud Storage location for a Dialogflow operation that writes or exports objects (e.g. exported agent or transcripts) outside of Dialogflow.
Settings for Generative AI.
Settings for Generative Fallback.
Prompt template.
Settings for knowledge connector. These parameters are used for LLM prompt like “You are . You are a helpful and verbose at , . Your task is to help humans on “.
Generators contain prompt to be sent to the LLM model to generate text. The prompt can contain parameters which will be resolved before calling the model. It can optionally contain banned phrases to ensure the model responses are safe.
Represents a custom placeholder in the prompt text.
The request message for EntityTypes.ImportEntityTypes.
The request message for Flows.ImportFlow.
The request message for Intents.ImportIntents.
The request message for TestCases.ImportTestCases.
Inline source for a Dialogflow operation that reads or imports objects (e.g. intents) into Dialogflow.
Instructs the speech recognizer on how to process the audio content.
An intent represents a user’s intent to interact with a conversational agent. You can provide information for the Dialogflow API to use to match user input to an intent by adding training phrases (i.e., examples of user input) to your intent.
Intent coverage represents the percentage of all possible intents in the agent that are triggered in any of a parent’s test cases.
The agent’s intent.
Represents the intent to trigger programmatically rather than as a result of natural language processing.
Represents an intent parameter.
Represents an example that the agent is trained on to identify the intent.
Represents a part of a training phrase.
The Knowledge Connector settings for this page or flow. This includes information such as the attached Knowledge Bases, and the way to execute fulfillment.
The response message for Agents.ListAgents.
The response message for Changelogs.ListChangelogs.
The response message for Environments.ListTestCaseResults.
The response message for Deployments.ListDeployments.
The response message for EntityTypes.ListEntityTypes.
The response message for Environments.ListEnvironments.
The response message for Experiments.ListExperiments.
The response message for Flows.ListFlows.
The response message for Generators.ListGenerators.
The response message for Intents.ListIntents.
The response message for Pages.ListPages.
The response message for SecuritySettings.ListSecuritySettings.
The response message for SessionEntityTypes.ListSessionEntityTypes.
The response message for TestCases.ListTestCaseResults.
The response message for TestCases.ListTestCases.
The response message for TransitionRouteGroups.ListTransitionRouteGroups.
The response message for Versions.ListVersions.
The response message for Webhooks.ListWebhooks.
The request message for Versions.LoadVersion.
The response message for Environments.LookupEnvironmentHistory.
Represents one match result of MatchIntent.
Request of MatchIntent.
Response of MatchIntent.
Settings related to NLU.
Instructs the speech synthesizer how to generate the output audio content.
A Dialogflow CX conversation (session) can be described and visualized as a state machine. The states of a CX session are represented by pages. For each flow, you define many pages, where your combined pages can handle a complete conversation on the topics the flow is designed for. At any given moment, exactly one page is the current page, the current page is considered active, and the flow associated with that page is considered active. Every flow has a special start page. When a flow initially becomes active, the start page page becomes the current page. For each conversational turn, the current page will either stay the same or transition to another page. You configure each page to collect information from the end-user that is relevant for the conversational state represented by the page. For more information, see the
Page guide.
Text input which can be used for prompt or banned phrases.
Represents the query input. It can contain one of: 1. A conversational query in the form of text. 2. An intent query that specifies which intent to trigger. 3. Natural language speech audio to be processed. 4. An event to be triggered. 5. DTMF digits to invoke an intent and fill in parameter value. 6. The results of a tool executed by the client.
Represents the parameters of a conversational query.
Represents the result of a conversational query.
Resource name and display name.
Represents a response message that can be returned by a conversational agent. Response messages are also used for output audio synthesis. The approach is as follows: * If at least one OutputAudioText response is present, then all OutputAudioText responses are linearly concatenated, and the result is used for output audio synthesis. * If the OutputAudioText responses are a mixture of text and SSML, then the concatenated result is treated as SSML; otherwise, the result is treated as either text or SSML as appropriate. The agent designer should ideally use either text or SSML consistently throughout the bot design. * Otherwise, all Text responses are linearly concatenated, and the result is used for output audio synthesis. This approach allows for more sophisticated user experience scenarios, where the text displayed to the user may differ from what is heard.
Indicates that the conversation succeeded, i.e., the bot handled the issue that the customer talked to it about. Dialogflow only uses this to determine which conversations should be counted as successful and doesn’t process the metadata in this message in any way. Note that Dialogflow also considers conversations that get to the conversation end page as successful even if they don’t return ConversationSuccess. You may set this, for example: * In the entry_fulfillment of a Page if entering the page indicates that the conversation succeeded. * In a webhook response when you determine that you handled the customer issue.
Indicates that interaction with the Dialogflow agent has ended. This message is generated by Dialogflow only and not supposed to be defined by the user.
Represents info card response. If the response contains generative knowledge prediction, Dialogflow will return a payload with Infobot Messenger compatible info card. Otherwise, the info card response is skipped.
Indicates that the conversation should be handed off to a live agent. Dialogflow only uses this to determine which conversations were handed off to a human agent for measurement purposes. What else to do with this signal is up to you and your handoff procedures. You may set this, for example: * In the entry_fulfillment of a Page if entering the page indicates something went extremely wrong in the conversation. * In a webhook response when you determine that the customer issue can only be handled by a human.
Represents an audio message that is composed of both segments synthesized from the Dialogflow agent prompts and ones hosted externally at the specified URIs. The external URIs are specified via play_audio. This message is generated by Dialogflow only and not supposed to be defined by the user.
Represents one segment of audio.
A text or ssml response that is preferentially used for TTS output audio synthesis, as described in the comment on the ResponseMessage message.
Specifies an audio clip to be played by the client as part of the response.
Represents the signal that telles the client to transfer the phone call connected to the agent to a third-party endpoint.
The text response message.
The request message for Agents.RestoreAgent.
Settings for restoring from a git branch
The configuration for auto rollout.
A single rollout step with specified traffic allocation.
State of the auto-rollout process.
The request message for Environments.RunContinuousTest.
The request message for TestCases.RunTestCase.
Settings for Generative Safety.
Text input which can be used for prompt or banned phrases.
Search configuration for UCS search queries.
Represents the settings related to security issues, such as data redaction and data retention. It may take hours for updates on the settings to propagate to all the related components and take effect.
Settings for exporting audio.
Settings for exporting conversations to
Insights.
The result of sentiment analysis. Sentiment analysis inspects user input and identifies the prevailing subjective opinion, especially to determine a user’s attitude as positive, negative, or neutral.
Session entity types are referred to as
User entity types and are entities that are built for an individual user such as favorites, preferences, playlists, and so on. You can redefine a session entity type at the session level to extend or replace a custom entity type at the user session level (we refer to the entity types defined at the agent level as “custom entity types”). Note: session entity types apply to all queries, regardless of the language. For more information about entity types, see the
Dialogflow documentation.
Settings related to speech recognition.
The request message for Experiments.StartExperiment.
The request message for Experiments.StopExperiment.
The request to set the feedback for a bot answer.
Configuration of how speech should be synthesized.
Represents a test case.
Represents a result from running a test case in an agent environment.
Represents configurations for a test case.
The description of differences between original and replayed agent output.
Represents the natural language text to be processed.
Settings related to speech synthesizing.
The request message for Flows.TrainFlow.
Transition coverage represents the percentage of all possible page transitions (page-level transition routes and event handlers, excluding transition route groups) present within any of a parent’s test cases.
A transition in a page.
The source or target of a transition.
A transition route specifies a intent that can be matched and/or a data condition that can be evaluated during a session. When a specified transition is matched, the following actions are taken in order: * If there is a trigger_fulfillment associated with the transition, it will be called. * If there is a target_page associated with the transition, the session will transition into the specified page. * If there is a target_flow associated with the transition, the session will transition into the specified flow.
A TransitionRouteGroup represents a group of TransitionRoutes to be used by a Page.
Transition route group coverage represents the percentage of all possible transition routes present within any of a parent’s test cases. The results are grouped by the transition route group.
Coverage result message for one transition route group.
A transition coverage in a transition route group.
The request message for Agents.ValidateAgent.
The request message for Flows.ValidateFlow.
Agent/flow validation message.
The history of variants update.
Represents a version of a flow.
A list of flow version variants.
A single flow version with specified traffic allocation.
Description of which voice to use for speech synthesis.
Webhooks host the developer’s business logic. During a session, webhooks allow the developer to use the data extracted by Dialogflow’s natural language processing to generate dynamic responses, validate collected data, or trigger actions on the backend.
Represents configuration for a generic web service.
The response message for Locations.ListLocations.
A resource that represents a Google Cloud location.
The response message for Operations.ListOperations.
This resource represents a long-running operation that is the result of a network API call.
A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
The
Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by
gRPC. Each
Status message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the
API Design Guide.
An object that represents a latitude/longitude pair. This is expressed as a pair of doubles to represent degrees latitude and degrees longitude. Unless specified otherwise, this object must conform to the WGS84 standard. Values must be within normalized ranges.
Retrieves the specified Changelog.
Returns the list of Changelogs.
Creates an agent in the specified location. Note: You should always train flows prior to sending them queries. See the
training documentation.
Deletes the specified agent.
Creates an entity type in the specified agent. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Deletes the specified entity type. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Exports the selected entity types.
Retrieves the specified entity type.
Imports the specified entitytypes into the agent.
Returns the list of all entity types in the specified agent.
Updates the specified entity type. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Fetches a list of continuous test results for a given environment.
Creates an Environment in the specified Agent. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: An empty
Struct message -
response: Environment
Deletes the specified Environment.
Deploys a flow to the specified Environment. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: DeployFlowMetadata -
response: DeployFlowResponse
Retrieves the specified Deployment.
Returns the list of all deployments in the specified Environment.
Creates an Experiment in the specified Environment.
Deletes the specified Experiment.
Retrieves the specified Experiment.
Returns the list of all experiments in the specified Environment.
Updates the specified Experiment.
Starts the specified Experiment. This rpc only changes the state of experiment from PENDING to RUNNING.
Stops the specified Experiment. This rpc only changes the state of experiment from RUNNING to DONE.
Retrieves the specified Environment.
Returns the list of all environments in the specified Agent.
Looks up the history of the specified Environment.
Updates the specified Environment. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: An empty
Struct message -
response: Environment
Kicks off a continuous test under the specified Environment. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: RunContinuousTestMetadata -
response: RunContinuousTestResponse
Processes a natural language query and returns structured, actionable data as a result. This method is not idempotent, because it may cause session entity types to be updated, which in turn might affect results of future queries. Note: Always use agent versions for production traffic. See
Versions and environments.
Creates a session entity type.
Deletes the specified session entity type.
Retrieves the specified session entity type.
Returns the list of all session entity types in the specified session.
Updates the specified session entity type.
Fulfills a matched intent returned by MatchIntent. Must be called after MatchIntent, with input from MatchIntentResponse. Otherwise, the behavior is undefined.
Returns preliminary intent match results, doesn’t change the session status.
Processes a natural language query and returns structured, actionable data as a result through server-side streaming. Server-side streaming allows Dialogflow to send
partial responses earlier in a single request.
Exports the specified agent to a binary file. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: An empty
Struct message -
response: ExportAgentResponse
Creates a flow in the specified agent. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Deletes a specified flow.
Exports the specified flow to a binary file. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: An empty
Struct message -
response: ExportFlowResponse Note that resources (e.g. intents, entities, webhooks) that the flow references will also be exported.
Retrieves the specified flow.
Gets the latest flow validation result. Flow validation is performed when ValidateFlow is called.
Imports the specified flow to the specified agent from a binary file. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: An empty
Struct message -
response: ImportFlowResponse Note: You should always train a flow prior to sending it queries. See the
training documentation.
Returns the list of all flows in the specified agent.
Creates a page in the specified flow. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Deletes the specified page. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Retrieves the specified page.
Returns the list of all pages in the specified flow.
Updates the specified page. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Updates the specified flow. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Trains the specified flow. Note that only the flow in ‘draft’ environment is trained. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: An empty
Struct message -
response: An
Empty message Note: You should always train a flow prior to sending it queries. See the
training documentation.
Creates an TransitionRouteGroup in the specified flow. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Deletes the specified TransitionRouteGroup. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Retrieves the specified TransitionRouteGroup.
Returns the list of all transition route groups in the specified flow.
Updates the specified TransitionRouteGroup. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Validates the specified flow and creates or updates validation results. Please call this API after the training is completed to get the complete validation results.
Compares the specified base version with target version.
Creates a Version in the specified Flow. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: CreateVersionOperationMetadata -
response: Version
Deletes the specified Version.
Retrieves the specified Version.
Returns the list of all versions in the specified Flow.
Updates the specified Version.
Creates a generator in the specified agent.
Deletes the specified generators.
Retrieves the specified generator.
Returns the list of all generators in the specified agent.
Update the specified generator.
Retrieves the specified agent.
Gets the generative settings for the agent.
Gets the latest agent validation result. Agent validation is performed when ValidateAgent is called.
Creates an intent in the specified agent. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Deletes the specified intent. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Exports the selected intents. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: ExportIntentsMetadata -
response: ExportIntentsResponse
Retrieves the specified intent.
Imports the specified intents into the agent. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: ImportIntentsMetadata -
response: ImportIntentsResponse
Returns the list of all intents in the specified agent.
Updates the specified intent. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Returns the list of all agents in the specified location.
Updates the specified agent. Note: You should always train flows prior to sending them queries. See the
training documentation.
Restores the specified agent from a binary file. Replaces the current agent with a new one. Note that all existing resources in agent (e.g. intents, entity types, flows) will be removed. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: An empty
Struct message -
response: An
Empty message Note: You should always train flows prior to sending them queries. See the
training documentation.
Processes a natural language query and returns structured, actionable data as a result. This method is not idempotent, because it may cause session entity types to be updated, which in turn might affect results of future queries. Note: Always use agent versions for production traffic. See
Versions and environments.
Creates a session entity type.
Deletes the specified session entity type.
Retrieves the specified session entity type.
Returns the list of all session entity types in the specified session.
Updates the specified session entity type.
Fulfills a matched intent returned by MatchIntent. Must be called after MatchIntent, with input from MatchIntentResponse. Otherwise, the behavior is undefined.
Returns preliminary intent match results, doesn’t change the session status.
Processes a natural language query and returns structured, actionable data as a result through server-side streaming. Server-side streaming allows Dialogflow to send
partial responses earlier in a single request.
Updates the feedback received from the user for a single turn of the bot response.
Batch deletes test cases.
Kicks off a batch run of test cases. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: BatchRunTestCasesMetadata -
response: BatchRunTestCasesResponse
Calculates the test coverage for an agent.
Creates a test case for the given agent.
Exports the test cases under the agent to a Cloud Storage bucket or a local file. Filter can be applied to export a subset of test cases. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: ExportTestCasesMetadata -
response: ExportTestCasesResponse
Gets a test case.
Imports the test cases from a Cloud Storage bucket or a local file. It always creates new test cases and won’t overwrite any existing ones. The provided ID in the imported test case is neglected. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: ImportTestCasesMetadata -
response: ImportTestCasesResponse
Fetches a list of test cases for a given agent.
Updates the specified test case.
Gets a test case result.
Fetches the list of run results for the given test case. A maximum of 100 results are kept for each test case.
Kicks off a test case run. This method is a
long-running operation. The returned
Operation type has the following method-specific fields: -
metadata: RunTestCaseMetadata -
response: RunTestCaseResponse
Creates an TransitionRouteGroup in the specified flow. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Deletes the specified TransitionRouteGroup. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Retrieves the specified TransitionRouteGroup.
Returns the list of all transition route groups in the specified flow.
Updates the specified TransitionRouteGroup. Note: You should always train a flow prior to sending it queries. See the
training documentation.
Updates the generative settings for the agent.
Validates the specified agent and creates or updates validation results. The agent in draft version is validated. Please call this API after the training is completed to get the complete validation results.
Creates a webhook in the specified agent.
Deletes the specified webhook.
Retrieves the specified webhook.
Returns the list of all webhooks in the specified agent.
Updates the specified webhook.
Gets information about a location.
Lists information about the supported locations for this service.
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. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to Code.CANCELLED.
Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.
Lists operations that match the specified filter in the request. If the server doesn’t support this method, it returns UNIMPLEMENTED.
Create security settings in the specified location.
Deletes the specified SecuritySettings.
Retrieves the specified SecuritySettings. The returned settings may be stale by up to 1 minute.
Returns the list of all security settings in the specified location.
Updates the specified SecuritySettings.
A builder providing access to all methods supported on
project resources.
It is not used directly, but through the
Dialogflow hub.
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. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to Code.CANCELLED.
Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.
Lists operations that match the specified filter in the request. If the server doesn’t support this method, it returns UNIMPLEMENTED.