PNG  IHDR;IDATxܻn0K )(pA 7LeG{ §㻢|ذaÆ 6lذaÆ 6lذaÆ 6lom$^yذag5bÆ 6lذaÆ 6lذa{ 6lذaÆ `}HFkm,mӪôô! x|'ܢ˟;E:9&ᶒ}{v]n&6 h_tڠ͵-ҫZ;Z$.Pkž)!o>}leQfJTu іچ\X=8Rن4`Vwl>nG^is"ms$ui?wbs[m6K4O.4%/bC%t Mז -lG6mrz2s%9s@-k9=)kB5\+͂Zsٲ Rn~GRC wIcIn7jJhۛNCS|j08yiHKֶۛkɈ+;SzL/F*\Ԕ#"5m2[S=gnaPeғL lذaÆ 6l^ḵaÆ 6lذaÆ 6lذa; _ذaÆ 6lذaÆ 6lذaÆ RIENDB` package Paws::LexRuntimeV2; use Moose; sub service { 'runtime-v2-lex' } sub signing_name { 'lex' } sub version { '2020-08-07' } sub flattened_arrays { 0 } has max_attempts => (is => 'ro', isa => 'Int', default => 5); has retry => (is => 'ro', isa => 'HashRef', default => sub { { base => 'rand', type => 'exponential', growth_factor => 2 } }); has retriables => (is => 'ro', isa => 'ArrayRef', default => sub { [ ] }); with 'Paws::API::Caller', 'Paws::API::EndpointResolver', 'Paws::Net::V4Signature', 'Paws::Net::RestJsonCaller'; sub DeleteSession { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LexRuntimeV2::DeleteSession', @_); return $self->caller->do_call($self, $call_object); } sub GetSession { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LexRuntimeV2::GetSession', @_); return $self->caller->do_call($self, $call_object); } sub PutSession { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LexRuntimeV2::PutSession', @_); return $self->caller->do_call($self, $call_object); } sub RecognizeText { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LexRuntimeV2::RecognizeText', @_); return $self->caller->do_call($self, $call_object); } sub RecognizeUtterance { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LexRuntimeV2::RecognizeUtterance', @_); return $self->caller->do_call($self, $call_object); } sub StartConversation { my $self = shift; my $call_object = $self->new_with_coercions('Paws::LexRuntimeV2::StartConversation', @_); return $self->caller->do_call($self, $call_object); } sub operations { qw/DeleteSession GetSession PutSession RecognizeText RecognizeUtterance StartConversation / } 1; ### main pod documentation begin ### =head1 NAME Paws::LexRuntimeV2 - Perl Interface to AWS Amazon Lex Runtime V2 =head1 SYNOPSIS use Paws; my $obj = Paws->service('LexRuntimeV2'); my $res = $obj->Method( Arg1 => $val1, Arg2 => [ 'V1', 'V2' ], # if Arg3 is an object, the HashRef will be used as arguments to the constructor # of the arguments type Arg3 => { Att1 => 'Val1' }, # if Arg4 is an array of objects, the HashRefs will be passed as arguments to # the constructor of the arguments type Arg4 => [ { Att1 => 'Val1' }, { Att1 => 'Val2' } ], ); =head1 DESCRIPTION For the AWS API documentation, see L =head1 METHODS =head2 DeleteSession =over =item BotAliasId => Str =item BotId => Str =item LocaleId => Str =item SessionId => Str =back Each argument is described in detail in: L Returns: a L instance Removes session information for a specified bot, alias, and user ID. You can use this operation to restart a conversation with a bot. When you remove a session, the entire history of the session is removed so that you can start again. You don't need to delete a session. Sessions have a time limit and will expire. Set the session time limit when you create the bot. The default is 5 minutes, but you can specify anything between 1 minute and 24 hours. If you specify a bot or alias ID that doesn't exist, you receive a C If the locale doesn't exist in the bot, or if the locale hasn't been enables for the alias, you receive a C. =head2 GetSession =over =item BotAliasId => Str =item BotId => Str =item LocaleId => Str =item SessionId => Str =back Each argument is described in detail in: L Returns: a L instance Returns session information for a specified bot, alias, and user. For example, you can use this operation to retrieve session information for a user that has left a long-running session in use. If the bot, alias, or session identifier doesn't exist, Amazon Lex V2 returns a C. If the locale doesn't exist or is not enabled for the alias, you receive a C. =head2 PutSession =over =item BotAliasId => Str =item BotId => Str =item LocaleId => Str =item SessionId => Str =item SessionState => L =item [Messages => ArrayRef[L]] =item [RequestAttributes => L] =item [ResponseContentType => Str] =back Each argument is described in detail in: L Returns: a L instance Creates a new session or modifies an existing session with an Amazon Lex V2 bot. Use this operation to enable your application to set the state of the bot. =head2 RecognizeText =over =item BotAliasId => Str =item BotId => Str =item LocaleId => Str =item SessionId => Str =item Text => Str =item [RequestAttributes => L] =item [SessionState => L] =back Each argument is described in detail in: L Returns: a L instance Sends user input to Amazon Lex V2. Client applications use this API to send requests to Amazon Lex V2 at runtime. Amazon Lex V2 then interprets the user input using the machine learning model that it build for the bot. In response, Amazon Lex V2 returns the next message to convey to the user and an optional response card to display. =head2 RecognizeUtterance =over =item BotAliasId => Str =item BotId => Str =item LocaleId => Str =item RequestContentType => Str =item SessionId => Str =item [InputStream => Str] =item [RequestAttributes => Str] =item [ResponseContentType => Str] =item [SessionState => Str] =back Each argument is described in detail in: L Returns: a L instance Sends user input to Amazon Lex V2. You can send text or speech. Clients use this API to send text and audio requests to Amazon Lex V2 at runtime. Amazon Lex V2 interprets the user input using the machine learning model built for the bot. The following request fields must be compressed with gzip and then base64 encoded before you send them to Amazon Lex V2. =over =item * requestAttributes =item * sessionState =back The following response fields are compressed using gzip and then base64 encoded by Amazon Lex V2. Before you can use these fields, you must decode and decompress them. =over =item * inputTranscript =item * interpretations =item * messages =item * requestAttributes =item * sessionState =back The example contains a Java application that compresses and encodes a Java object to send to Amazon Lex V2, and a second that decodes and decompresses a response from Amazon Lex V2. =head2 StartConversation =over =item BotAliasId => Str =item BotId => Str =item LocaleId => Str =item RequestEventStream => L =item SessionId => Str =item [ConversationMode => Str] =back Each argument is described in detail in: L Returns: a L instance Starts an HTTP/2 bidirectional event stream that enables you to send audio, text, or DTMF input in real time. After your application starts a conversation, users send input to Amazon Lex V2 as a stream of events. Amazon Lex V2 processes the incoming events and responds with streaming text or audio events. Audio input must be in the following format: C