LexRuntimeService.Client.post_content(**kwargs)¶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:
PizzaSize ): "What size pizza would you like?".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:
x-amz-lex-dialog-state header set to ElicitSlotx-amz-lex-intent-name header set to the intent name in the current contextx-amz-lex-slot-to-elicit header set to the slot name for which the message is eliciting informationx-amz-lex-slots header set to a map of slots configured for the intent with their current valuesx-amz-lex-dialog-state header is set to Confirmation and the x-amz-lex-slot-to-elicit header is omitted.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 Documentation
Request Syntax
response = client.post_content(
botName='string',
botAlias='string',
userId='string',
sessionAttributes={...}|[...]|123|123.4|'string'|True|None,
requestAttributes={...}|[...]|123|123.4|'string'|True|None,
contentType='string',
accept='string',
inputStream=b'bytes'|file,
activeContexts={...}|[...]|123|123.4|'string'|True|None
)
[REQUIRED]
Name of the Amazon Lex bot.
[REQUIRED]
Alias of the Amazon Lex bot.
[REQUIRED]
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.
userID field must not contain any personally identifiable information of the user, for example, name, personal identification numbers, or other end user personal information.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.
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.
[REQUIRED]
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:
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.
text/plain; charset=utf-8 , Amazon Lex returns text in the response.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.audio/pcm , the speech returned is audio/pcm in 16-bit, little endian format.[REQUIRED]
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.
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.
dict
Response Syntax
{
'contentType': 'string',
'intentName': 'string',
'nluIntentConfidence': {...}|[...]|123|123.4|'string'|True|None,
'alternativeIntents': {...}|[...]|123|123.4|'string'|True|None,
'slots': {...}|[...]|123|123.4|'string'|True|None,
'sessionAttributes': {...}|[...]|123|123.4|'string'|True|None,
'sentimentResponse': 'string',
'message': 'string',
'encodedMessage': 'string',
'messageFormat': 'PlainText'|'CustomPayload'|'SSML'|'Composite',
'dialogState': 'ElicitIntent'|'ConfirmIntent'|'ElicitSlot'|'Fulfilled'|'ReadyForFulfillment'|'Failed',
'slotToElicit': 'string',
'inputTranscript': 'string',
'encodedInputTranscript': 'string',
'audioStream': StreamingBody(),
'botVersion': 'string',
'sessionId': 'string',
'activeContexts': {...}|[...]|123|123.4|'string'|True|None
}
Response Structure
(dict) --
contentType (string) --
Content type as specified in the Accept HTTP header in the request.
intentName (string) --
Current user intent that Amazon Lex is aware of.
nluIntentConfidence (JSON serializable) --
Provides a score that indicates how confident Amazon Lex is that the returned intent is the one that matches the user's intent. The score is between 0.0 and 1.0.
The score is a relative score, not an absolute score. The score may change based on improvements to Amazon Lex.
alternativeIntents (JSON serializable) --
One to four alternative intents that may be applicable to the user's intent.
Each alternative includes a score that indicates how confident Amazon Lex is that the intent matches the user's intent. The intents are sorted by the confidence score.
slots (JSON serializable) --
Map of zero or more intent slots (name/value pairs) Amazon Lex detected from the user input during the conversation. The field is base-64 encoded.
Amazon Lex creates a resolution list containing likely values for a slot. The value that it returns is determined by the valueSelectionStrategy selected when the slot type was created or updated. If valueSelectionStrategy is set to ORIGINAL_VALUE , the value provided by the user is returned, if the user value is similar to the slot values. If valueSelectionStrategy is set to TOP_RESOLUTION Amazon Lex returns the first value in the resolution list or, if there is no resolution list, null. If you don't specify a valueSelectionStrategy , the default is ORIGINAL_VALUE .
sessionAttributes (JSON serializable) --
Map of key/value pairs representing the session-specific context information.
sentimentResponse (string) --
The sentiment expressed in an utterance.
When the bot is configured to send utterances to Amazon Comprehend for sentiment analysis, this field contains the result of the analysis.
message (string) --
You can only use this field in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR, and it-IT locales. In all other locales, the message field is null. You should use the encodedMessage field instead.
The message to convey to the user. The message can come from the bot's configuration or from a Lambda function.
If the intent is not configured with a Lambda function, or if the Lambda function returned Delegate as the dialogAction.type in its response, Amazon Lex decides on the next course of action and selects an appropriate message from the bot's configuration based on the current interaction context. For example, if Amazon Lex isn't able to understand user input, it uses a clarification prompt message.
When you create an intent you can assign messages to groups. When messages are assigned to groups Amazon Lex returns one message from each group in the response. The message field is an escaped JSON string containing the messages. For more information about the structure of the JSON string returned, see msg-prompts-formats.
If the Lambda function returns a message, Amazon Lex passes it to the client in its response.
encodedMessage (string) --
The message to convey to the user. The message can come from the bot's configuration or from a Lambda function.
If the intent is not configured with a Lambda function, or if the Lambda function returned Delegate as the dialogAction.type in its response, Amazon Lex decides on the next course of action and selects an appropriate message from the bot's configuration based on the current interaction context. For example, if Amazon Lex isn't able to understand user input, it uses a clarification prompt message.
When you create an intent you can assign messages to groups. When messages are assigned to groups Amazon Lex returns one message from each group in the response. The message field is an escaped JSON string containing the messages. For more information about the structure of the JSON string returned, see msg-prompts-formats.
If the Lambda function returns a message, Amazon Lex passes it to the client in its response.
The encodedMessage field is base-64 encoded. You must decode the field before you can use the value.
messageFormat (string) --
The format of the response message. One of the following values:
PlainText - The message contains plain UTF-8 text.CustomPayload - The message is a custom format for the client.SSML - The message contains text formatted for voice output.Composite - The message contains an escaped JSON object containing one or more messages from the groups that messages were assigned to when the intent was created.dialogState (string) --
Identifies the current state of the user interaction. Amazon Lex returns one of the following values as dialogState . The client can optionally use this information to customize the user interface.
ElicitIntent - Amazon Lex wants to elicit the user's intent. Consider the following examples: For example, a user might utter an intent ("I want to order a pizza"). If Amazon Lex cannot infer the user intent from this utterance, it will return this dialog state.ConfirmIntent - Amazon Lex is expecting a "yes" or "no" response. For example, Amazon Lex wants user confirmation before fulfilling an intent. Instead of a simple "yes" or "no" response, a user might respond with additional information. For example, "yes, but make it a thick crust pizza" or "no, I want to order a drink." Amazon Lex can process such additional information (in these examples, update the crust type slot or change the intent from OrderPizza to OrderDrink).ElicitSlot - Amazon Lex is expecting the value of a slot for the current intent. For example, suppose that in the response Amazon Lex sends this message: "What size pizza would you like?". A user might reply with the slot value (e.g., "medium"). The user might also provide additional information in the response (e.g., "medium thick crust pizza"). Amazon Lex can process such additional information appropriately.Fulfilled - Conveys that the Lambda function has successfully fulfilled the intent.ReadyForFulfillment - Conveys that the client has to fulfill the request.Failed - Conveys that the conversation with the user failed. This can happen for various reasons, including that the user does not provide an appropriate response to prompts from the service (you can configure how many times Amazon Lex can prompt a user for specific information), or if the Lambda function fails to fulfill the intent.slotToElicit (string) --
If the dialogState value is ElicitSlot , returns the name of the slot for which Amazon Lex is eliciting a value.
inputTranscript (string) --
The text used to process the request.
You can use this field only in the de-DE, en-AU, en-GB, en-US, es-419, es-ES, es-US, fr-CA, fr-FR, and it-IT locales. In all other locales, the inputTranscript field is null. You should use the encodedInputTranscript field instead.
If the input was an audio stream, the inputTranscript field contains the text extracted from the audio stream. This is the text that is actually processed to recognize intents and slot values. You can use this information to determine if Amazon Lex is correctly processing the audio that you send.
encodedInputTranscript (string) --
The text used to process the request.
If the input was an audio stream, the encodedInputTranscript field contains the text extracted from the audio stream. This is the text that is actually processed to recognize intents and slot values. You can use this information to determine if Amazon Lex is correctly processing the audio that you send.
The encodedInputTranscript field is base-64 encoded. You must decode the field before you can use the value.
audioStream (StreamingBody) --
The prompt (or statement) to convey to the user. This is based on the bot configuration and context. For example, if Amazon Lex did not understand the user intent, it sends the clarificationPrompt configured for the bot. If the intent requires confirmation before taking the fulfillment action, it sends the confirmationPrompt . Another example: Suppose that the Lambda function successfully fulfilled the intent, and sent a message to convey to the user. Then Amazon Lex sends that message in the response.
botVersion (string) --
The version of the bot that responded to the conversation. You can use this information to help determine if one version of a bot is performing better than another version.
sessionId (string) --
The unique identifier for the session.
activeContexts (JSON serializable) --
A list of active contexts for the session. A context can be set when an intent is fulfilled or by calling the PostContent , PostText , or PutSession operation.
You can use a context to control the intents that can follow up an intent, or to modify the operation of your application.
Exceptions
LexRuntimeService.Client.exceptions.NotFoundExceptionLexRuntimeService.Client.exceptions.BadRequestExceptionLexRuntimeService.Client.exceptions.LimitExceededExceptionLexRuntimeService.Client.exceptions.InternalFailureExceptionLexRuntimeService.Client.exceptions.ConflictExceptionLexRuntimeService.Client.exceptions.UnsupportedMediaTypeExceptionLexRuntimeService.Client.exceptions.NotAcceptableExceptionLexRuntimeService.Client.exceptions.RequestTimeoutExceptionLexRuntimeService.Client.exceptions.DependencyFailedExceptionLexRuntimeService.Client.exceptions.BadGatewayExceptionLexRuntimeService.Client.exceptions.LoopDetectedException