const completionSpec = { name : "lex-runtime" , description : '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,' , subcommands : [ { name : "delete-session" , description : "Removes session information for a specified bot, alias, and user ID" , options : [ { name : "--bot-name" , description : "The name of the bot that contains the session data" , args : { name : "string" , } , } , { name : "--bot-alias" , description : "The alias in use for the bot that contains the session data" , args : { name : "string" , } , } , { name : "--user-id" , description : "The identifier of the user associated with the session data" , args : { name : "string" , } , } , { name : "--cli-input-json" , description : "Performs service operation based on the JSON string provided. The JSON string follows the format provided by ``--generate-cli-skeleton``. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally" , args : { name : "string" , } , } , { name : "--generate-cli-skeleton" , description : "Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value ``input``, prints a sample input JSON that can be used as an argument for ``--cli-input-json``. If provided with the value ``output``, it validates the command inputs and returns a sample output JSON for that command" , args : { name : "string" , suggestions : [ "input" , "output" ] , } , } , ] , } , { name : "get-session" , description : "Returns session information for a specified bot, alias, and user ID" , options : [ { name : "--bot-name" , description : "The name of the bot that contains the session data" , args : { name : "string" , } , } , { name : "--bot-alias" , description : "The alias in use for the bot that contains the session data" , args : { name : "string" , } , } , { name : "--user-id" , description : "The ID of the client application user. Amazon Lex uses this to identify a user's conversation with your bot" , args : { name : "string" , } , } , { name : "--checkpoint-label-filter" , description : "A string used to filter the intents returned in the recentIntentSummaryView structure.  When you specify a filter, only intents with their checkpointLabel field set to that string are returned" , args : { name : "string" , } , } , { name : "--cli-input-json" , description : "Performs service operation based on the JSON string provided. The JSON string follows the format provided by ``--generate-cli-skeleton``. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally" , args : { name : "string" , } , } , { name : "--generate-cli-skeleton" , description : "Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value ``input``, prints a sample input JSON that can be used as an argument for ``--cli-input-json``. If provided with the value ``output``, it validates the command inputs and returns a sample output JSON for that command" , args : { name : "string" , suggestions : [ "input" , "output" ] , } , } , ] , } , { name : "post-content" , description : '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' , options : [ { name : "--bot-name" , description : "Name of the Amazon Lex bot" , args : { name : "string" , } , } , { name : "--bot-alias" , description : "Alias of the Amazon Lex bot" , args : { name : "string" , } , } , { name : "--user-id" , description : "The ID of the client application user. Amazon Lex uses this to identify a user's conversation with your bot. At runtime, each request must contain the userID field. To decide the user ID to use for your application, consider the following factors.   The userID field must not contain any personally identifiable information of the user, for example, name, personal identification numbers, or other end user personal information.   If you want a user to start a conversation on one device and continue on another device, use a user-specific identifier.   If you want the same user to be able to have two independent conversations on two different devices, choose a device-specific identifier.   A user can't have two independent conversations with two different versions of the same bot. For example, a user can't have a conversation with the PROD and BETA versions of the same bot. If you anticipate that a user will need to have conversation with two different versions, for example, while testing, include the bot alias in the user ID to separate the two conversations" , args : { name : "string" , } , } , { name : "--session-attributes" , description : "You pass this value as the x-amz-lex-session-attributes HTTP header. Application-specific information passed between Amazon Lex and a client application. The value must be a JSON serialized and base64 encoded map with string keys and values. The total size of the sessionAttributes and requestAttributes headers is limited to 12 KB. For more information, see Setting Session Attributes" , args : { name : "string" , } , } , { name : "--request-attributes" , description : "You pass this value as the x-amz-lex-request-attributes HTTP header. Request-specific information passed between Amazon Lex and a client application. The value must be a JSON serialized and base64 encoded map with string keys and values. The total size of the requestAttributes and sessionAttributes headers is limited to 12 KB. The namespace x-amz-lex: is reserved for special attributes. Don't create any request attributes with the prefix x-amz-lex:. For more information, see Setting Request Attributes" , args : { name : "string" , } , } , { name : "--content-type" , description : "You pass this value as the Content-Type HTTP header.   Indicates the audio format or text. The header value must start with one of the following prefixes:    PCM format, audio data must be in little-endian byte order.   audio/l16; rate=16000; channels=1   audio/x-l16; sample-rate=16000; channel-count=1   audio/lpcm; sample-rate=8000; sample-size-bits=16; channel-count=1; is-big-endian=false      Opus format   audio/x-cbr-opus-with-preamble; preamble-size=0; bit-rate=256000; frame-size-milliseconds=4     Text format   text/plain; charset=utf-8" , args : { name : "string" , } , } , { name : "--accept" , description : "You pass this value as the Accept HTTP header.   The message Amazon Lex returns in the response can be either text or speech based on the Accept HTTP header value in the request.     If the value is text/plain; charset=utf-8, Amazon Lex returns text in the response.     If the value begins with audio/, Amazon Lex returns speech in the response. Amazon Lex uses Amazon Polly to generate the speech (using the configuration you specified in the Accept header). For example, if you specify audio/mpeg as the value, Amazon Lex returns speech in the MPEG format.   If the value is audio/pcm, the speech returned is audio/pcm in 16-bit, little endian format.    The following are the accepted values:   audio/mpeg   audio/ogg   audio/pcm   text/plain; charset=utf-8   audio/* (defaults to mpeg)" , args : { name : "string" , } , } , { name : "--input-stream" , description : "User input in PCM or Opus audio format or text format as described in the Content-Type HTTP header.  You can stream audio data to Amazon Lex or you can create a local buffer that captures all of the audio data before sending. In general, you get better performance if you stream audio data rather than buffering the data locally" , args : { name : "blob" , } , } , { name : "--active-contexts" , description : "A list of contexts active for the request. A context can be activated when a previous intent is fulfilled, or by including the context in the request, If you don't specify a list of contexts, Amazon Lex will use the current list of contexts for the session. If you specify an empty list, all contexts for the session are cleared" , args : { name : "string" , } , } , { name : "outfile" , description : "Filename where the content will be saved" , args : { name : "string" , } , } , ] , } , { name : "post-text" , description : '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' , options : [ { name : "--bot-name" , description : "The name of the Amazon Lex bot" , args : { name : "string" , } , } , { name : "--bot-alias" , description : "The alias of the Amazon Lex bot" , args : { name : "string" , } , } , { name : "--user-id" , description : "The ID of the client application user. Amazon Lex uses this to identify a user's conversation with your bot. At runtime, each request must contain the userID field. To decide the user ID to use for your application, consider the following factors.   The userID field must not contain any personally identifiable information of the user, for example, name, personal identification numbers, or other end user personal information.   If you want a user to start a conversation on one device and continue on another device, use a user-specific identifier.   If you want the same user to be able to have two independent conversations on two different devices, choose a device-specific identifier.   A user can't have two independent conversations with two different versions of the same bot. For example, a user can't have a conversation with the PROD and BETA versions of the same bot. If you anticipate that a user will need to have conversation with two different versions, for example, while testing, include the bot alias in the user ID to separate the two conversations" , args : { name : "string" , } , } , { name : "--session-attributes" , description : "Application-specific information passed between Amazon Lex and a client application. For more information, see Setting Session Attributes" , args : { name : "map" , } , } , { name : "--request-attributes" , description : "Request-specific information passed between Amazon Lex and a client application. The namespace x-amz-lex: is reserved for special attributes. Don't create any request attributes with the prefix x-amz-lex:. For more information, see Setting Request Attributes" , args : { name : "map" , } , } , { name : "--input-text" , description : "The text that the user entered (Amazon Lex interprets this text)" , args : { name : "string" , } , } , { name : "--active-contexts" , description : "A list of contexts active for the request. A context can be activated when a previous intent is fulfilled, or by including the context in the request, If you don't specify a list of contexts, Amazon Lex will use the current list of contexts for the session. If you specify an empty list, all contexts for the session are cleared" , args : { name : "list" , } , } , { name : "--cli-input-json" , description : "Performs service operation based on the JSON string provided. The JSON string follows the format provided by ``--generate-cli-skeleton``. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally" , args : { name : "string" , } , } , { name : "--generate-cli-skeleton" , description : "Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value ``input``, prints a sample input JSON that can be used as an argument for ``--cli-input-json``. If provided with the value ``output``, it validates the command inputs and returns a sample output JSON for that command" , args : { name : "string" , suggestions : [ "input" , "output" ] , } , } , ] , } , { name : "put-session" , description : "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" , options : [ { name : "--bot-name" , description : "The name of the bot that contains the session data" , args : { name : "string" , } , } , { name : "--bot-alias" , description : "The alias in use for the bot that contains the session data" , args : { name : "string" , } , } , { name : "--user-id" , description : "The ID of the client application user. Amazon Lex uses this to identify a user's conversation with your bot" , args : { name : "string" , } , } , { name : "--session-attributes" , description : "Map of key/value pairs representing the session-specific context information. It contains application information passed between Amazon Lex and a client application" , args : { name : "map" , } , } , { name : "--dialog-action" , description : "Sets the next action that the bot should take to fulfill the conversation" , args : { name : "structure" , } , } , { name : "--recent-intent-summary-view" , description : "A summary of the recent intents for the bot. You can use the intent summary view to set a checkpoint label on an intent and modify attributes of intents. You can also use it to remove or add intent summary objects to the list. An intent that you modify or add to the list must make sense for the bot. For example, the intent name must be valid for the bot. You must provide valid values for:    intentName    slot names    slotToElict    If you send the recentIntentSummaryView parameter in a PutSession request, the contents of the new summary view replaces the old summary view. For example, if a GetSession request returns three intents in the summary view and you call PutSession with one intent in the summary view, the next call to GetSession will only return one intent" , args : { name : "list" , } , } , { name : "--accept" , description : "The message that Amazon Lex returns in the response can be either text or speech based depending on the value of this field.   If the value is text/plain; charset=utf-8, Amazon Lex returns text in the response.   If the value begins with audio/, Amazon Lex returns speech in the response. Amazon Lex uses Amazon Polly to generate the speech in the configuration that you specify. For example, if you specify audio/mpeg as the value, Amazon Lex returns speech in the MPEG format.   If the value is audio/pcm, the speech is returned as audio/pcm in 16-bit, little endian format.   The following are the accepted values:    audio/mpeg     audio/ogg     audio/pcm     audio/* (defaults to mpeg)    text/plain; charset=utf-8" , args : { name : "string" , } , } , { name : "--active-contexts" , description : "A list of contexts active for the request. A context can be activated when a previous intent is fulfilled, or by including the context in the request, If you don't specify a list of contexts, Amazon Lex will use the current list of contexts for the session. If you specify an empty list, all contexts for the session are cleared" , args : { name : "list" , } , } , { name : "outfile" , description : "Filename where the content will be saved" , args : { name : "string" , } , } , ] , } , ] , } ; export default completionSpec ;