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package OpenAI::API::Request::Embedding; |
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use strict; |
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use Moo; |
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use strictures 2; |
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extends 'OpenAI::API::Request'; |
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use Types::Standard qw(Bool Str Num Int Map); |
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has model => ( is => 'rw', isa => Str, required => 1, ); |
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has input => ( is => 'rw', isa => Str, required => 1, ); |
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has user => ( is => 'rw', isa => Str, ); |
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sub endpoint { 'embeddings' } |
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sub method { 'POST' } |
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1; |
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__END__ |
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=head1 NAME |
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OpenAI::API::Request::Embedding - embeddings endpoint |
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=head1 SYNOPSIS |
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use OpenAI::API::Request::Embedding; |
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my $request = OpenAI::API::Request::Embedding->new( |
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model => "text-embedding-ada-002", |
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input => "The food was delicious and the waiter...", |
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); |
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my $res = $request->send(); |
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=head1 DESCRIPTION |
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Get a vector representation of a given input that can be easily consumed |
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by machine learning models and algorithms. |
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=head1 METHODS |
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=head2 new() |
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=over 4 |
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=item * model |
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=item * input |
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=item * user [optional] |
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=back |
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=head2 send() |
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Sends the request and returns a data structured similar to the one |
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documented in the API reference. |
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=head2 send_async() |
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Send a request asynchronously. Returns a L<future|IO::Async::Future> that will |
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be resolved with the decoded JSON response. See L<OpenAI::API::Request> |
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for an example. |
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=head1 SEE ALSO |
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OpenAI API Reference: L<Embeddings|https://platform.openai.com/docs/api-reference/embeddings> |