AI-Embedding

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README  view on Meta::CPAN

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INSTALLATION

To install this module, run the following commands:

	perl Makefile.PL
	make
	make test
	make install

SUPPORT AND DOCUMENTATION

After installing, you can find documentation for this module with the
perldoc command.

    perldoc AI::Embedding

You can also look for information at:

    RT, CPAN's request tracker (report bugs here)
        https://rt.cpan.org/NoAuth/Bugs.html?Dist=AI-Embedding

    CPAN Ratings
        https://cpanratings.perl.org/d/AI-Embedding

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

Returns true if the last method call was successful

=head2 error

Returns the last error message or an empty string if B<success> returned true

=head2 embedding

    my $csv_embedding = $embedding->embedding('Some text passage', [$verbose]);

Generates an embedding for the given text and returns it as a comma-separated string. The C<embedding> method takes a single parameter, the text to generate the embedding for.

Returns a (rather long) string that can be stored in a C<TEXT> database field.

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 raw_embedding

    my @raw_embedding = $embedding->raw_embedding('Some text passage', [$verbose]);

Generates an embedding for the given text and returns it as an array. The C<raw_embedding> method takes a single parameter, the text to generate the embedding for.

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

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.

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


    my $cmp = $embedding->comparator($csv_embedding2);
    my $similarity = $cmp->($csv_embedding1);

See L</"Comparator">

The returned method reference returns the cosine similarity between the Embedding used to call the C<comparator> method and the Embedding supplied to the method reference.  See L<compare> for an explanation of the cosine similarity.

=head2 compare

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

Compares two embeddings and returns the cosine similarity between them. The B<compare> method takes two parameters: $csv_embedding1 and $csv_embedding2 (both comma-separated embedding strings).

Returns the cosine similarity as a floating-point number between -1 and 1, where 1 represents identical embeddings, 0 represents no similarity, and -1 represents opposite embeddings.

The absolute number is not usually relevant for text comparision.  It is usually sufficient to rank the comparison results in order of high to low to reflect the best match to the worse match.

=head1 SEE ALSO

L<https://openai.com> - OpenAI official website

=head1 AUTHOR

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

Ian Boddison <ian at boddison.com>

=head1 BUGS

Please report any bugs or feature requests to C<bug-ai-embedding at rt.cpan.org>, or through
the web interface at L<https://rt.cpan.org/NoAuth/ReportBug.html?Queue=bug-ai-embedding>.  I will be notified, and then you'll
automatically be notified of progress on your bug as I make changes.

=head1 SUPPORT

You can find documentation for this module with the perldoc command.

    perldoc AI::Embedding

You can also look for information at:

=over 4

=item * RT: CPAN's request tracker (report bugs here)

L<https://rt.cpan.org/NoAuth/Bugs.html?Dist=AI-Embedding>