view release on metacpan or  search on metacpan

lib/AI/Embedding.pm  view on Meta::CPAN

    my $similarity = $cmp->($csv_embedding1);
    my $similarity_with_other_embedding = $embedding->compare($csv_embedding1, $csv_embedding2);

=head1 DESCRIPTION

The L<AI::Embedding> module provides an interface for working with text embeddings using various APIs. It currently supports the L<OpenAI|https://www.openai.com> L<Embeddings API|https://platform.openai.com/docs/guides/embeddings/what-are-embeddings>...

Embeddings allow the meaning of passages of text to be compared for similarity.  This is more natural and useful to humans than using traditional keyword based comparisons.

An Embedding is a multi-dimensional vector representing the meaning of a piece of text.  The Embedding vector is created by an AI Model.  The default model (OpenAI's C<text-embedding-ada-002>) produces a 1536 dimensional vector.  The resulting vector...

=head2 Comparator

Embeddings are used to compare similarity of meaning between two passages of text.  A typical work case is to store a number of pieces of text (e.g. articles or blogs) in a database and compare each one to some user supplied search text.  L<AI::Embed...

Alternatively, the C<comparator> method can be called with one Embedding.  The C<comparator> returns a reference to a method that takes a single Embedding to be compared to the Embedding from which the Comparator was created.

When comparing multiple Embeddings to the same Embedding (such as search text) it is faster to use a C<comparator>.

=head1 CONSTRUCTOR

lib/AI/Embedding.pm  view on Meta::CPAN

Parameters:

=over

=item *

C<key> - B<required> The API Key

=item *

C<api> - The API to use.  Currently only 'OpenAI' is supported and this is the default.

=item *

C<model> - The language model to use.  Defaults to C<text-embedding-ada-002> - see L<OpenAI docs|https://platform.openai.com/docs/guides/embeddings/what-are-embeddings>

=back

=head1 METHODS

=head2 success

lib/AI/Embedding.pm  view on Meta::CPAN

If the method call fails it sets the L</"error"> message and returns C<undef>.  If the optional C<verbose> parameter is true, the complete L<HTTP::Tiny> response object is also returned to aid with debugging issues when using this module.

=head2 test_embedding

    my $test_embedding = $embedding->test_embedding('Some text passage', $dimensions);

Used for testing code without making a chargeable call to the API.

Provides a CSV string of the same size and format as L<embedding> but with meaningless random data.

Returns a random embedding.  Both parameters are optional.  If a text string is provided, the returned embedding will always be the same random embedding otherwise it will be random and different every time.  The C<dimension> parameter controls the n...

=head2 comparator

    $embedding->comparator($csv_embedding2);

Sets a vector as a C<comparator> for future comparisons and returns a reference to a method for using the C<comparator>.

The B<comparator> method takes a single parameter, the comma-separated Embedding string to use as the comparator.

The following two are functionally equivalent.  However, where multiple Embeddings are to be compared to a single Embedding, using a L<Comparator> is significantly faster.