pub struct Client { /* private fields */ }
Expand description
Client for Amazon Lex Runtime Service
Client for invoking operations on Amazon Lex Runtime Service. Each operation on Amazon Lex Runtime Service is a method on this
this struct. .send()
MUST be invoked on the generated operations to dispatch the request to the service.
§Constructing a Client
A Config
is required to construct a client. For most use cases, the aws-config
crate should be used to automatically resolve this config using
aws_config::load_from_env()
, since this will resolve an SdkConfig
which can be shared
across multiple different AWS SDK clients. This config resolution process can be customized
by calling aws_config::from_env()
instead, which returns a ConfigLoader
that uses
the builder pattern to customize the default config.
In the simplest case, creating a client looks as follows:
let config = aws_config::load_from_env().await;
let client = aws_sdk_lexruntime::Client::new(&config);
Occasionally, SDKs may have additional service-specific values that can be set on the Config
that
is absent from SdkConfig
, or slightly different settings for a specific client may be desired.
The Builder
struct implements From<&SdkConfig>
, so setting these specific settings can be
done as follows:
let sdk_config = ::aws_config::load_from_env().await;
let config = aws_sdk_lexruntime::config::Builder::from(&sdk_config)
.some_service_specific_setting("value")
.build();
See the aws-config
docs and Config
for more information on customizing configuration.
Note: Client construction is expensive due to connection thread pool initialization, and should be done once at application start-up.
§Using the Client
A client has a function for every operation that can be performed by the service.
For example, the DeleteSession
operation has
a Client::delete_session
, function which returns a builder for that operation.
The fluent builder ultimately has a send()
function that returns an async future that
returns a result, as illustrated below:
let result = client.delete_session()
.bot_name("example")
.send()
.await;
The underlying HTTP requests that get made by this can be modified with the customize_operation
function on the fluent builder. See the customize
module for more
information.
Implementations§
Source§impl Client
impl Client
Sourcepub fn delete_session(&self) -> DeleteSessionFluentBuilder
pub fn delete_session(&self) -> DeleteSessionFluentBuilder
Constructs a fluent builder for the DeleteSession
operation.
- The fluent builder is configurable:
bot_name(impl Into<String>)
/set_bot_name(Option<String>)
:
required: trueThe name of the bot that contains the session data.
bot_alias(impl Into<String>)
/set_bot_alias(Option<String>)
:
required: trueThe alias in use for the bot that contains the session data.
user_id(impl Into<String>)
/set_user_id(Option<String>)
:
required: trueThe identifier of the user associated with the session data.
- On success, responds with
DeleteSessionOutput
with field(s):bot_name(Option<String>)
:The name of the bot associated with the session data.
bot_alias(Option<String>)
:The alias in use for the bot associated with the session data.
user_id(Option<String>)
:The ID of the client application user.
session_id(Option<String>)
:The unique identifier for the session.
- On failure, responds with
SdkError<DeleteSessionError>
Source§impl Client
impl Client
Sourcepub fn get_session(&self) -> GetSessionFluentBuilder
pub fn get_session(&self) -> GetSessionFluentBuilder
Constructs a fluent builder for the GetSession
operation.
- The fluent builder is configurable:
bot_name(impl Into<String>)
/set_bot_name(Option<String>)
:
required: trueThe name of the bot that contains the session data.
bot_alias(impl Into<String>)
/set_bot_alias(Option<String>)
:
required: trueThe alias in use for the bot that contains the session data.
user_id(impl Into<String>)
/set_user_id(Option<String>)
:
required: trueThe ID of the client application user. Amazon Lex uses this to identify a user’s conversation with your bot.
checkpoint_label_filter(impl Into<String>)
/set_checkpoint_label_filter(Option<String>)
:
required: falseA 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.
- On success, responds with
GetSessionOutput
with field(s):recent_intent_summary_view(Option<Vec::<IntentSummary>>)
:An array of information about the intents used in the session. The array can contain a maximum of three summaries. If more than three intents are used in the session, the
recentIntentSummaryView
operation contains information about the last three intents used.If you set the
checkpointLabelFilter
parameter in the request, the array contains only the intents with the specified label.session_attributes(Option<HashMap::<String, String>>)
:Map of key/value pairs representing the session-specific context information. It contains application information passed between Amazon Lex and a client application.
session_id(Option<String>)
:A unique identifier for the session.
dialog_action(Option<DialogAction>)
:Describes the current state of the bot.
active_contexts(Option<Vec::<ActiveContext>>)
:A list of active contexts for the session. A context can be set when an intent is fulfilled or by calling the
PostContent
,PostText
, orPutSession
operation.You can use a context to control the intents that can follow up an intent, or to modify the operation of your application.
- On failure, responds with
SdkError<GetSessionError>
Source§impl Client
impl Client
Sourcepub fn post_content(&self) -> PostContentFluentBuilder
pub fn post_content(&self) -> PostContentFluentBuilder
Constructs a fluent builder for the PostContent
operation.
- The fluent builder is configurable:
bot_name(impl Into<String>)
/set_bot_name(Option<String>)
:
required: trueName of the Amazon Lex bot.
bot_alias(impl Into<String>)
/set_bot_alias(Option<String>)
:
required: trueAlias of the Amazon Lex bot.
user_id(impl Into<String>)
/set_user_id(Option<String>)
:
required: trueThe 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.
-
session_attributes(impl Into<String>)
/set_session_attributes(Option<String>)
:
required: falseYou 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
andrequestAttributes
headers is limited to 12 KB.For more information, see Setting Session Attributes.
request_attributes(impl Into<String>)
/set_request_attributes(Option<String>)
:
required: falseYou 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
andsessionAttributes
headers is limited to 12 KB.The namespace
x-amz-lex:
is reserved for special attributes. Don’t create any request attributes with the prefixx-amz-lex:
.For more information, see Setting Request Attributes.
content_type(impl Into<String>)
/set_content_type(Option<String>)
:
required: trueYou 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
-
-
accept(impl Into<String>)
/set_accept(Option<String>)
:
required: falseYou 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 theAccept
header). For example, if you specifyaudio/mpeg
as the value, Amazon Lex returns speech in the MPEG format. -
If the value is
audio/pcm
, the speech returned isaudio/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)
-
-
input_stream(ByteStream)
/set_input_stream(ByteStream)
:
required: trueUser 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.
active_contexts(impl Into<String>)
/set_active_contexts(Option<String>)
:
required: falseA 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.
- On success, responds with
PostContentOutput
with field(s):content_type(Option<String>)
:Content type as specified in the
Accept
HTTP header in the request.intent_name(Option<String>)
:Current user intent that Amazon Lex is aware of.
nlu_intent_confidence(Option<String>)
: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.
alternative_intents(Option<String>)
: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(Option<String>)
: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. IfvalueSelectionStrategy
is set toORIGINAL_VALUE
, the value provided by the user is returned, if the user value is similar to the slot values. IfvalueSelectionStrategy
is set toTOP_RESOLUTION
Amazon Lex returns the first value in the resolution list or, if there is no resolution list, null. If you don’t specify avalueSelectionStrategy
, the default isORIGINAL_VALUE
.session_attributes(Option<String>)
:Map of key/value pairs representing the session-specific context information.
sentiment_response(Option<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(Option<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 theencodedMessage
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 thedialogAction.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.
encoded_message(Option<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 thedialogAction.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.message_format(Option<MessageFormatType>)
: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.
-
dialog_state(Option<DialogState>)
: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.
-
slot_to_elicit(Option<String>)
:If the
dialogState
value isElicitSlot
, returns the name of the slot for which Amazon Lex is eliciting a value.input_transcript(Option<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 theencodedInputTranscript
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.encoded_input_transcript(Option<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.audio_stream(ByteStream)
: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 theconfirmationPrompt
. 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.bot_version(Option<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.
session_id(Option<String>)
:The unique identifier for the session.
active_contexts(Option<String>)
:A list of active contexts for the session. A context can be set when an intent is fulfilled or by calling the
PostContent
,PostText
, orPutSession
operation.You can use a context to control the intents that can follow up an intent, or to modify the operation of your application.
- On failure, responds with
SdkError<PostContentError>
Source§impl Client
impl Client
Sourcepub fn post_text(&self) -> PostTextFluentBuilder
pub fn post_text(&self) -> PostTextFluentBuilder
Constructs a fluent builder for the PostText
operation.
- The fluent builder is configurable:
bot_name(impl Into<String>)
/set_bot_name(Option<String>)
:
required: trueThe name of the Amazon Lex bot.
bot_alias(impl Into<String>)
/set_bot_alias(Option<String>)
:
required: trueThe alias of the Amazon Lex bot.
user_id(impl Into<String>)
/set_user_id(Option<String>)
:
required: trueThe 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.
-
session_attributes(impl Into<String>, impl Into<String>)
/set_session_attributes(Option<HashMap::<String, String>>)
:
required: falseApplication-specific information passed between Amazon Lex and a client application.
For more information, see Setting Session Attributes.
request_attributes(impl Into<String>, impl Into<String>)
/set_request_attributes(Option<HashMap::<String, String>>)
:
required: falseRequest-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 prefixx-amz-lex:
.For more information, see Setting Request Attributes.
input_text(impl Into<String>)
/set_input_text(Option<String>)
:
required: trueThe text that the user entered (Amazon Lex interprets this text).
active_contexts(ActiveContext)
/set_active_contexts(Option<Vec::<ActiveContext>>)
:
required: falseA 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.
- On success, responds with
PostTextOutput
with field(s):intent_name(Option<String>)
:The current user intent that Amazon Lex is aware of.
nlu_intent_confidence(Option<IntentConfidence>)
: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. For more information, see Confidence Scores.
The score is a relative score, not an absolute score. The score may change based on improvements to Amazon Lex.
alternative_intents(Option<Vec::<PredictedIntent>>)
: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(Option<HashMap::<String, String>>)
:The intent slots that Amazon Lex detected from the user input in the conversation.
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. IfvalueSelectionStrategy
is set toORIGINAL_VALUE
, the value provided by the user is returned, if the user value is similar to the slot values. IfvalueSelectionStrategy
is set toTOP_RESOLUTION
Amazon Lex returns the first value in the resolution list or, if there is no resolution list, null. If you don’t specify avalueSelectionStrategy
, the default isORIGINAL_VALUE
.session_attributes(Option<HashMap::<String, String>>)
:A map of key-value pairs representing the session-specific context information.
message(Option<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 thedialogAction.type
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.
sentiment_response(Option<SentimentResponse>)
:The sentiment expressed in and utterance.
When the bot is configured to send utterances to Amazon Comprehend for sentiment analysis, this field contains the result of the analysis.
message_format(Option<MessageFormatType>)
: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 defined by the Lambda function. -
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.
-
dialog_state(Option<DialogState>)
: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 user intent.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 dialogState.
-
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,” a user might respond with additional information. For example, “yes, but make it 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 value, or change intent from OrderPizza to OrderDrink).
-
ElicitSlot
- Amazon Lex is expecting a slot value 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 configured for the intent has successfully fulfilled the intent. -
ReadyForFulfillment
- Conveys that the client has to fulfill the intent. -
Failed
- Conveys that the conversation with the user failed.This can happen for various reasons including that the user did 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 the Lambda function failed to fulfill the intent.
-
slot_to_elicit(Option<String>)
:If the
dialogState
value isElicitSlot
, returns the name of the slot for which Amazon Lex is eliciting a value.response_card(Option<ResponseCard>)
:Represents the options that the user has to respond to the current prompt. Response Card can come from the bot configuration (in the Amazon Lex console, choose the settings button next to a slot) or from a code hook (Lambda function).
session_id(Option<String>)
:A unique identifier for the session.
bot_version(Option<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.
active_contexts(Option<Vec::<ActiveContext>>)
:A list of active contexts for the session. A context can be set when an intent is fulfilled or by calling the
PostContent
,PostText
, orPutSession
operation.You can use a context to control the intents that can follow up an intent, or to modify the operation of your application.
- On failure, responds with
SdkError<PostTextError>
Source§impl Client
impl Client
Sourcepub fn put_session(&self) -> PutSessionFluentBuilder
pub fn put_session(&self) -> PutSessionFluentBuilder
Constructs a fluent builder for the PutSession
operation.
- The fluent builder is configurable:
bot_name(impl Into<String>)
/set_bot_name(Option<String>)
:
required: trueThe name of the bot that contains the session data.
bot_alias(impl Into<String>)
/set_bot_alias(Option<String>)
:
required: trueThe alias in use for the bot that contains the session data.
user_id(impl Into<String>)
/set_user_id(Option<String>)
:
required: trueThe ID of the client application user. Amazon Lex uses this to identify a user’s conversation with your bot.
session_attributes(impl Into<String>, impl Into<String>)
/set_session_attributes(Option<HashMap::<String, String>>)
:
required: falseMap of key/value pairs representing the session-specific context information. It contains application information passed between Amazon Lex and a client application.
dialog_action(DialogAction)
/set_dialog_action(Option<DialogAction>)
:
required: falseSets the next action that the bot should take to fulfill the conversation.
recent_intent_summary_view(IntentSummary)
/set_recent_intent_summary_view(Option<Vec::<IntentSummary>>)
:
required: falseA 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 aPutSession
request, the contents of the new summary view replaces the old summary view. For example, if aGetSession
request returns three intents in the summary view and you callPutSession
with one intent in the summary view, the next call toGetSession
will only return one intent.-
accept(impl Into<String>)
/set_accept(Option<String>)
:
required: falseThe 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 specifyaudio/mpeg
as the value, Amazon Lex returns speech in the MPEG format. -
If the value is
audio/pcm
, the speech is returned asaudio/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
-
-
active_contexts(ActiveContext)
/set_active_contexts(Option<Vec::<ActiveContext>>)
:
required: falseA 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.
- On success, responds with
PutSessionOutput
with field(s):content_type(Option<String>)
:Content type as specified in the
Accept
HTTP header in the request.intent_name(Option<String>)
:The name of the current intent.
slots(Option<String>)
:Map of zero or more intent slots Amazon Lex detected from the user input during the conversation.
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. IfvalueSelectionStrategy
is set toORIGINAL_VALUE
, the value provided by the user is returned, if the user value is similar to the slot values. IfvalueSelectionStrategy
is set toTOP_RESOLUTION
Amazon Lex returns the first value in the resolution list or, if there is no resolution list, null. If you don’t specify avalueSelectionStrategy
the default isORIGINAL_VALUE
.session_attributes(Option<String>)
:Map of key/value pairs representing session-specific context information.
message(Option<String>)
:The next message that should be presented to the user.
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 theencodedMessage
field instead.encoded_message(Option<String>)
:The next message that should be presented to the user.
The
encodedMessage
field is base-64 encoded. You must decode the field before you can use the value.message_format(Option<MessageFormatType>)
: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.
-
dialog_state(Option<DialogState>)
:-
ConfirmIntent
- Amazon Lex is expecting a “yes” or “no” response to confirm the intent before fulfilling an intent. -
ElicitIntent
- Amazon Lex wants to elicit the user’s intent. -
ElicitSlot
- Amazon Lex is expecting the value of a slot for the current intent. -
Failed
- Conveys that the conversation with the user has failed. This can happen for various reasons, including the user does not provide an appropriate response to prompts from the service, or if the Lambda function fails to fulfill the intent. -
Fulfilled
- Conveys that the Lambda function has sucessfully fulfilled the intent. -
ReadyForFulfillment
- Conveys that the client has to fulfill the intent.
-
slot_to_elicit(Option<String>)
:If the
dialogState
isElicitSlot
, returns the name of the slot for which Amazon Lex is eliciting a value.audio_stream(ByteStream)
:The audio version of the message to convey to the user.
session_id(Option<String>)
:A unique identifier for the session.
active_contexts(Option<String>)
:A list of active contexts for the session.
- On failure, responds with
SdkError<PutSessionError>
Source§impl Client
impl Client
Sourcepub fn from_conf(conf: Config) -> Self
pub fn from_conf(conf: Config) -> Self
Creates a new client from the service Config
.
§Panics
This method will panic in the following cases:
- Retries or timeouts are enabled without a
sleep_impl
configured. - Identity caching is enabled without a
sleep_impl
andtime_source
configured. - No
behavior_version
is provided.
The panic message for each of these will have instructions on how to resolve them.
Source§impl Client
impl Client
Sourcepub fn new(sdk_config: &SdkConfig) -> Self
pub fn new(sdk_config: &SdkConfig) -> Self
Creates a new client from an SDK Config.
§Panics
- This method will panic if the
sdk_config
is missing an async sleep implementation. If you experience this panic, set thesleep_impl
on the Config passed into this function to fix it. - This method will panic if the
sdk_config
is missing an HTTP connector. If you experience this panic, set thehttp_connector
on the Config passed into this function to fix it. - This method will panic if no
BehaviorVersion
is provided. If you experience this panic, setbehavior_version
on the Config or enable thebehavior-version-latest
Cargo feature.
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