/** * Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. * SPDX-License-Identifier: Apache-2.0. */ #pragma once #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace Aws { namespace Http { class HttpClient; class HttpClientFactory; } // namespace Http namespace Utils { template< typename R, typename E> class Outcome; namespace Threading { class Executor; } // namespace Threading } // namespace Utils namespace Auth { class AWSCredentials; class AWSCredentialsProvider; } // namespace Auth namespace Client { class RetryStrategy; } // namespace Client namespace LexRuntimeService { namespace Model { class DeleteSessionRequest; class GetSessionRequest; class PostContentRequest; class PostTextRequest; class PutSessionRequest; typedef Aws::Utils::Outcome DeleteSessionOutcome; typedef Aws::Utils::Outcome GetSessionOutcome; typedef Aws::Utils::Outcome PostContentOutcome; typedef Aws::Utils::Outcome PostTextOutcome; typedef Aws::Utils::Outcome PutSessionOutcome; typedef std::future DeleteSessionOutcomeCallable; typedef std::future GetSessionOutcomeCallable; typedef std::future PostContentOutcomeCallable; typedef std::future PostTextOutcomeCallable; typedef std::future PutSessionOutcomeCallable; } // namespace Model class LexRuntimeServiceClient; typedef std::function&) > DeleteSessionResponseReceivedHandler; typedef std::function&) > GetSessionResponseReceivedHandler; typedef std::function&) > PostContentResponseReceivedHandler; typedef std::function&) > PostTextResponseReceivedHandler; typedef std::function&) > PutSessionResponseReceivedHandler; /** *

Amazon Lex provides both build and runtime endpoints. Each endpoint provides * a set of operations (API). Your conversational bot uses the runtime API to * understand user utterances (user input text or voice). For example, suppose a * user says "I want pizza", your bot sends this input to Amazon Lex using the * runtime API. Amazon Lex recognizes that the user request is for the OrderPizza * intent (one of the intents defined in the bot). Then Amazon Lex engages in user * conversation on behalf of the bot to elicit required information (slot values, * such as pizza size and crust type), and then performs fulfillment activity (that * you configured when you created the bot). You use the build-time API to create * and manage your Amazon Lex bot. For a list of build-time operations, see the * build-time API, .

*/ class AWS_LEXRUNTIMESERVICE_API LexRuntimeServiceClient : public Aws::Client::AWSJsonClient { public: typedef Aws::Client::AWSJsonClient BASECLASS; /** * Initializes client to use DefaultCredentialProviderChain, with default http client factory, and optional client config. If client config * is not specified, it will be initialized to default values. */ LexRuntimeServiceClient(const Aws::Client::ClientConfiguration& clientConfiguration = Aws::Client::ClientConfiguration()); /** * Initializes client to use SimpleAWSCredentialsProvider, with default http client factory, and optional client config. If client config * is not specified, it will be initialized to default values. */ LexRuntimeServiceClient(const Aws::Auth::AWSCredentials& credentials, const Aws::Client::ClientConfiguration& clientConfiguration = Aws::Client::ClientConfiguration()); /** * Initializes client to use specified credentials provider with specified client config. If http client factory is not supplied, * the default http client factory will be used */ LexRuntimeServiceClient(const std::shared_ptr& credentialsProvider, const Aws::Client::ClientConfiguration& clientConfiguration = Aws::Client::ClientConfiguration()); virtual ~LexRuntimeServiceClient(); /** *

Removes session information for a specified bot, alias, and user ID. *

See Also:

AWS * API Reference

*/ virtual Model::DeleteSessionOutcome DeleteSession(const Model::DeleteSessionRequest& request) const; /** *

Removes session information for a specified bot, alias, and user ID. *

See Also:

AWS * API Reference

* * returns a future to the operation so that it can be executed in parallel to other requests. */ virtual Model::DeleteSessionOutcomeCallable DeleteSessionCallable(const Model::DeleteSessionRequest& request) const; /** *

Removes session information for a specified bot, alias, and user ID. *

See Also:

AWS * API Reference

* * Queues the request into a thread executor and triggers associated callback when operation has finished. */ virtual void DeleteSessionAsync(const Model::DeleteSessionRequest& request, const DeleteSessionResponseReceivedHandler& handler, const std::shared_ptr& context = nullptr) const; /** *

Returns session information for a specified bot, alias, and user * ID.

See Also:

AWS * API Reference

*/ virtual Model::GetSessionOutcome GetSession(const Model::GetSessionRequest& request) const; /** *

Returns session information for a specified bot, alias, and user * ID.

See Also:

AWS * API Reference

* * returns a future to the operation so that it can be executed in parallel to other requests. */ virtual Model::GetSessionOutcomeCallable GetSessionCallable(const Model::GetSessionRequest& request) const; /** *

Returns session information for a specified bot, alias, and user * ID.

See Also:

AWS * API Reference

* * Queues the request into a thread executor and triggers associated callback when operation has finished. */ virtual void GetSessionAsync(const Model::GetSessionRequest& request, const GetSessionResponseReceivedHandler& handler, const std::shared_ptr& context = nullptr) const; /** *

Sends user input (text or speech) to Amazon Lex. Clients use this API to * send text and audio requests to Amazon Lex at runtime. Amazon Lex interprets the * user input using the machine learning model that it built for the bot.

*

The PostContent operation supports audio input at 8kHz and * 16kHz. You can use 8kHz audio to achieve higher speech recognition accuracy in * telephone audio applications.

In response, Amazon Lex returns the next * message to convey to the user. Consider the following example messages:

*
  • For a user input "I would like a pizza," Amazon Lex might return a * response with a message eliciting slot data (for example, * PizzaSize): "What size pizza would you like?".

  • * After the user provides all of the pizza order information, Amazon Lex might * return a response with a message to get user confirmation: "Order the pizza?". *

  • After the user replies "Yes" to the confirmation prompt, * Amazon Lex might return a conclusion statement: "Thank you, your cheese pizza * has been ordered.".

Not all Amazon Lex messages require a * response from the user. For example, conclusion statements do not require a * response. Some messages require only a yes or no response. In addition to the * message, Amazon Lex provides additional context about the message * in the response that you can use to enhance client behavior, such as displaying * the appropriate client user interface. Consider the following examples:

*
  • If the message is to elicit slot data, Amazon Lex returns the * following context information:

    • * x-amz-lex-dialog-state header set to ElicitSlot

      *
    • x-amz-lex-intent-name header set to the intent name * in the current context

    • x-amz-lex-slot-to-elicit * header set to the slot name for which the message is eliciting * information

    • x-amz-lex-slots header set to a map * of slots configured for the intent with their current values

    *
  • If the message is a confirmation prompt, the * x-amz-lex-dialog-state header is set to Confirmation * and the x-amz-lex-slot-to-elicit header is omitted.

  • *

    If the message is a clarification prompt configured for the intent, * indicating that the user intent is not understood, the * x-amz-dialog-state header is set to ElicitIntent and * the x-amz-slot-to-elicit header is omitted.

In * addition, Amazon Lex also returns your application-specific * sessionAttributes. For more information, see Managing * Conversation Context.

See Also:

AWS * API Reference

*/ virtual Model::PostContentOutcome PostContent(const Model::PostContentRequest& request) const; /** *

Sends user input (text or speech) to Amazon Lex. Clients use this API to * send text and audio requests to Amazon Lex at runtime. Amazon Lex interprets the * user input using the machine learning model that it built for the bot.

*

The PostContent operation supports audio input at 8kHz and * 16kHz. You can use 8kHz audio to achieve higher speech recognition accuracy in * telephone audio applications.

In response, Amazon Lex returns the next * message to convey to the user. Consider the following example messages:

*
  • For a user input "I would like a pizza," Amazon Lex might return a * response with a message eliciting slot data (for example, * PizzaSize): "What size pizza would you like?".

  • * After the user provides all of the pizza order information, Amazon Lex might * return a response with a message to get user confirmation: "Order the pizza?". *

  • After the user replies "Yes" to the confirmation prompt, * Amazon Lex might return a conclusion statement: "Thank you, your cheese pizza * has been ordered.".

Not all Amazon Lex messages require a * response from the user. For example, conclusion statements do not require a * response. Some messages require only a yes or no response. In addition to the * message, Amazon Lex provides additional context about the message * in the response that you can use to enhance client behavior, such as displaying * the appropriate client user interface. Consider the following examples:

*
  • If the message is to elicit slot data, Amazon Lex returns the * following context information:

    • * x-amz-lex-dialog-state header set to ElicitSlot

      *
    • x-amz-lex-intent-name header set to the intent name * in the current context

    • x-amz-lex-slot-to-elicit * header set to the slot name for which the message is eliciting * information

    • x-amz-lex-slots header set to a map * of slots configured for the intent with their current values

    *
  • If the message is a confirmation prompt, the * x-amz-lex-dialog-state header is set to Confirmation * and the x-amz-lex-slot-to-elicit header is omitted.

  • *

    If the message is a clarification prompt configured for the intent, * indicating that the user intent is not understood, the * x-amz-dialog-state header is set to ElicitIntent and * the x-amz-slot-to-elicit header is omitted.

In * addition, Amazon Lex also returns your application-specific * sessionAttributes. For more information, see Managing * Conversation Context.

See Also:

AWS * API Reference

* * returns a future to the operation so that it can be executed in parallel to other requests. */ virtual Model::PostContentOutcomeCallable PostContentCallable(const Model::PostContentRequest& request) const; /** *

Sends user input (text or speech) to Amazon Lex. Clients use this API to * send text and audio requests to Amazon Lex at runtime. Amazon Lex interprets the * user input using the machine learning model that it built for the bot.

*

The PostContent operation supports audio input at 8kHz and * 16kHz. You can use 8kHz audio to achieve higher speech recognition accuracy in * telephone audio applications.

In response, Amazon Lex returns the next * message to convey to the user. Consider the following example messages:

*
  • For a user input "I would like a pizza," Amazon Lex might return a * response with a message eliciting slot data (for example, * PizzaSize): "What size pizza would you like?".

  • * After the user provides all of the pizza order information, Amazon Lex might * return a response with a message to get user confirmation: "Order the pizza?". *

  • After the user replies "Yes" to the confirmation prompt, * Amazon Lex might return a conclusion statement: "Thank you, your cheese pizza * has been ordered.".

Not all Amazon Lex messages require a * response from the user. For example, conclusion statements do not require a * response. Some messages require only a yes or no response. In addition to the * message, Amazon Lex provides additional context about the message * in the response that you can use to enhance client behavior, such as displaying * the appropriate client user interface. Consider the following examples:

*
  • If the message is to elicit slot data, Amazon Lex returns the * following context information:

    • * x-amz-lex-dialog-state header set to ElicitSlot

      *
    • x-amz-lex-intent-name header set to the intent name * in the current context

    • x-amz-lex-slot-to-elicit * header set to the slot name for which the message is eliciting * information

    • x-amz-lex-slots header set to a map * of slots configured for the intent with their current values

    *
  • If the message is a confirmation prompt, the * x-amz-lex-dialog-state header is set to Confirmation * and the x-amz-lex-slot-to-elicit header is omitted.

  • *

    If the message is a clarification prompt configured for the intent, * indicating that the user intent is not understood, the * x-amz-dialog-state header is set to ElicitIntent and * the x-amz-slot-to-elicit header is omitted.

In * addition, Amazon Lex also returns your application-specific * sessionAttributes. For more information, see Managing * Conversation Context.

See Also:

AWS * API Reference

* * Queues the request into a thread executor and triggers associated callback when operation has finished. */ virtual void PostContentAsync(const Model::PostContentRequest& request, const PostContentResponseReceivedHandler& handler, const std::shared_ptr& context = nullptr) const; /** *

Sends user input to Amazon Lex. Client applications can use this API to send * requests to Amazon Lex at runtime. Amazon Lex then interprets the user input * using the machine learning model it built for the bot.

In response, * Amazon Lex returns the next message to convey to the user an * optional responseCard to display. Consider the following example * messages:

  • For a user input "I would like a pizza", Amazon Lex * might return a response with a message eliciting slot data (for example, * PizzaSize): "What size pizza would you like?"

  • After the user * provides all of the pizza order information, Amazon Lex might return a response * with a message to obtain user confirmation "Proceed with the pizza order?".

    *
  • After the user replies to a confirmation prompt with a "yes", * Amazon Lex might return a conclusion statement: "Thank you, your cheese pizza * has been ordered.".

Not all Amazon Lex messages require a * user response. For example, a conclusion statement does not require a response. * Some messages require only a "yes" or "no" user response. In addition to the * message, Amazon Lex provides additional context about the message * in the response that you might use to enhance client behavior, for example, to * display the appropriate client user interface. These are the * slotToElicit, dialogState, intentName, * and slots fields in the response. Consider the following examples: *

  • If the message is to elicit slot data, Amazon Lex returns the * following context information:

    • dialogState set to * ElicitSlot

    • intentName set to the intent name in * the current context

    • slotToElicit set to the * slot name for which the message is eliciting information

    • *
    • slots set to a map of slots, configured for the intent, * with currently known values

  • If the message is a * confirmation prompt, the dialogState is set to ConfirmIntent and * SlotToElicit is set to null.

  • If the message is a * clarification prompt (configured for the intent) that indicates that user intent * is not understood, the dialogState is set to ElicitIntent and * slotToElicit is set to null.

In addition, * Amazon Lex also returns your application-specific * sessionAttributes. For more information, see Managing * Conversation Context.

See Also:

AWS * API Reference

*/ virtual Model::PostTextOutcome PostText(const Model::PostTextRequest& request) const; /** *

Sends user input to Amazon Lex. Client applications can use this API to send * requests to Amazon Lex at runtime. Amazon Lex then interprets the user input * using the machine learning model it built for the bot.

In response, * Amazon Lex returns the next message to convey to the user an * optional responseCard to display. Consider the following example * messages:

  • For a user input "I would like a pizza", Amazon Lex * might return a response with a message eliciting slot data (for example, * PizzaSize): "What size pizza would you like?"

  • After the user * provides all of the pizza order information, Amazon Lex might return a response * with a message to obtain user confirmation "Proceed with the pizza order?".

    *
  • After the user replies to a confirmation prompt with a "yes", * Amazon Lex might return a conclusion statement: "Thank you, your cheese pizza * has been ordered.".

Not all Amazon Lex messages require a * user response. For example, a conclusion statement does not require a response. * Some messages require only a "yes" or "no" user response. In addition to the * message, Amazon Lex provides additional context about the message * in the response that you might use to enhance client behavior, for example, to * display the appropriate client user interface. These are the * slotToElicit, dialogState, intentName, * and slots fields in the response. Consider the following examples: *

  • If the message is to elicit slot data, Amazon Lex returns the * following context information:

    • dialogState set to * ElicitSlot

    • intentName set to the intent name in * the current context

    • slotToElicit set to the * slot name for which the message is eliciting information

    • *
    • slots set to a map of slots, configured for the intent, * with currently known values

  • If the message is a * confirmation prompt, the dialogState is set to ConfirmIntent and * SlotToElicit is set to null.

  • If the message is a * clarification prompt (configured for the intent) that indicates that user intent * is not understood, the dialogState is set to ElicitIntent and * slotToElicit is set to null.

In addition, * Amazon Lex also returns your application-specific * sessionAttributes. For more information, see Managing * Conversation Context.

See Also:

AWS * API Reference

* * returns a future to the operation so that it can be executed in parallel to other requests. */ virtual Model::PostTextOutcomeCallable PostTextCallable(const Model::PostTextRequest& request) const; /** *

Sends user input to Amazon Lex. Client applications can use this API to send * requests to Amazon Lex at runtime. Amazon Lex then interprets the user input * using the machine learning model it built for the bot.

In response, * Amazon Lex returns the next message to convey to the user an * optional responseCard to display. Consider the following example * messages:

  • For a user input "I would like a pizza", Amazon Lex * might return a response with a message eliciting slot data (for example, * PizzaSize): "What size pizza would you like?"

  • After the user * provides all of the pizza order information, Amazon Lex might return a response * with a message to obtain user confirmation "Proceed with the pizza order?".

    *
  • After the user replies to a confirmation prompt with a "yes", * Amazon Lex might return a conclusion statement: "Thank you, your cheese pizza * has been ordered.".

Not all Amazon Lex messages require a * user response. For example, a conclusion statement does not require a response. * Some messages require only a "yes" or "no" user response. In addition to the * message, Amazon Lex provides additional context about the message * in the response that you might use to enhance client behavior, for example, to * display the appropriate client user interface. These are the * slotToElicit, dialogState, intentName, * and slots fields in the response. Consider the following examples: *

  • If the message is to elicit slot data, Amazon Lex returns the * following context information:

    • dialogState set to * ElicitSlot

    • intentName set to the intent name in * the current context

    • slotToElicit set to the * slot name for which the message is eliciting information

    • *
    • slots set to a map of slots, configured for the intent, * with currently known values

  • If the message is a * confirmation prompt, the dialogState is set to ConfirmIntent and * SlotToElicit is set to null.

  • If the message is a * clarification prompt (configured for the intent) that indicates that user intent * is not understood, the dialogState is set to ElicitIntent and * slotToElicit is set to null.

In addition, * Amazon Lex also returns your application-specific * sessionAttributes. For more information, see Managing * Conversation Context.

See Also:

AWS * API Reference

* * Queues the request into a thread executor and triggers associated callback when operation has finished. */ virtual void PostTextAsync(const Model::PostTextRequest& request, const PostTextResponseReceivedHandler& handler, const std::shared_ptr& context = nullptr) const; /** *

Creates a new session or modifies an existing session with an Amazon Lex bot. * Use this operation to enable your application to set the state of the bot.

*

For more information, see Managing * Sessions.

See Also:

AWS * API Reference

*/ virtual Model::PutSessionOutcome PutSession(const Model::PutSessionRequest& request) const; /** *

Creates a new session or modifies an existing session with an Amazon Lex bot. * Use this operation to enable your application to set the state of the bot.

*

For more information, see Managing * Sessions.

See Also:

AWS * API Reference

* * returns a future to the operation so that it can be executed in parallel to other requests. */ virtual Model::PutSessionOutcomeCallable PutSessionCallable(const Model::PutSessionRequest& request) const; /** *

Creates a new session or modifies an existing session with an Amazon Lex bot. * Use this operation to enable your application to set the state of the bot.

*

For more information, see Managing * Sessions.

See Also:

AWS * API Reference

* * Queues the request into a thread executor and triggers associated callback when operation has finished. */ virtual void PutSessionAsync(const Model::PutSessionRequest& request, const PutSessionResponseReceivedHandler& handler, const std::shared_ptr& context = nullptr) const; void OverrideEndpoint(const Aws::String& endpoint); private: void init(const Aws::Client::ClientConfiguration& clientConfiguration); void DeleteSessionAsyncHelper(const Model::DeleteSessionRequest& request, const DeleteSessionResponseReceivedHandler& handler, const std::shared_ptr& context) const; void GetSessionAsyncHelper(const Model::GetSessionRequest& request, const GetSessionResponseReceivedHandler& handler, const std::shared_ptr& context) const; void PostContentAsyncHelper(const Model::PostContentRequest& request, const PostContentResponseReceivedHandler& handler, const std::shared_ptr& context) const; void PostTextAsyncHelper(const Model::PostTextRequest& request, const PostTextResponseReceivedHandler& handler, const std::shared_ptr& context) const; void PutSessionAsyncHelper(const Model::PutSessionRequest& request, const PutSessionResponseReceivedHandler& handler, const std::shared_ptr& context) const; Aws::String m_uri; Aws::String m_configScheme; std::shared_ptr m_executor; }; } // namespace LexRuntimeService } // namespace Aws