Text::SubParsers

Raku package for extracting and processing of interpret-able sub-strings in texts.

The primary motivation for creating this package is the post-processing of the outputs of Large Language Models (LLMs), [AA1, AAp1, AAp2, AAp3].

Installation

From Zef ecosystem:

zef install Text::SubParsers

From GitHub:

zef install https://github.com/antononcube/Raku-Text-SubParsers.git

Usage examples

Date extractions

Here we extract dates from a text:

use Text::SubParsers;
my $res = "Openheimer's birthday is April 22, 1905 or April 2, 1905, as far as I know.";

Text::SubParsers::Core.new('DateTime').subparse($res).raku;

Compare with the result of the parse method over the same text:

say Text::SubParsers::Core.new('DateTime').parse($res);

Here are the results of both subparse and parse on string that is a valid date specification:

Text::SubParsers::Core.new('DateTime').subparse('April 22, 1905');

Text::SubParsers::Core.new('DateTime').parse('April 22, 1905');

Sub-parsing with user supplied subs

Instead of using Text::SubParsers::Core.new the functions sub-parser and exact-parser can be used.

Here is an example of using:

• Invocation of sub-parser

• (Sub-)parsing with a user supplied function (sub)

sub known-cities(Str $x) { 
    $x ∈ ['Seattle', 'Chicago', 'New York', 'Sao Paulo', 'Miami', 'Los Angeles'] ?? $x.uc !! Nil 
}

sub-parser(&known-cities).subparse("
1. New York City, NY - 8,804,190
2. Los Angeles, CA - 3,976,322
3. Chicago, IL - 2,746,388
4. Houston, TX - 2,304,580
5. Philadelphia, PA - 1,608,162
6. San Antonio, TX - 1,5
")

Here is the "full form" of the last result

_.raku

Sub-parsing with WhateverCode

With the parser spec WhateverCode an attempt is made to extract dates, JSON expressions, numbers, and Booleans (in that order). Here is an example:

sub-parser(WhateverCode).subparse('
Is it true that the JSON expression {"date": "2023-03-08", "rationalNumber": "11/3"} contains the date 2023-03-08 and the rational number 11/3?
').raku

Different types of input

The input given to the sub-parsers can be a:

• String

• Array of strings

• Map with string values

Here is an example with an array of strings:

sub-parser(WhateverCode).subparse(['{a:3, y:45}', "2023-08-06", "Mass 1,503lbs"]).raku

Here is an example with a Map:

sub-parser('JSON').subparse({1 => '{ "ui" : 3, "io" : 78}', 2 => '{ "GA" : 34, "CA" : 178}'}).raku

Failed parsing

If the given texts cannot be parsed Failure objects are returned. This allows the payload of failure's Exception object to be examined and see the inputs to the sub-parsers:

my $fres = sub-parser(DateTime).subparse('Some date [1930, 2, 14].');
$fres.raku

Here is the structure of the exception's payload:

$fres.exception.payload

Using a soft Exception (i.e. a Failure object) is useful when (i) the sub-parsing is part of a certain pipeline of operations and (ii) the input to the sub-parser is "hard to compute" (the result of a lengthy or expensive computation.) Instead of just giving a message "cannot parse" or similar the returned Failure object allows examination of the input and error.

Processing LLM outputs

As it was mentioned above, the primary motivation for creating this package is the post-processing of the outputs of Large Language Models (LLMs), [AA1, AAp1, AAp2, AAp3].

Here is an example of creating a LLM-function and its invocation over a string:

use LLM::Functions;

my &fs = llm-function(
        {"What is the average speed of $_ ?"},
        llm-evaluator => llm-configuration(
                'PaLM',
                prompts => 'You are knowledgeable engineer and you give concise, numeric answers.'));

say &fs('car in USA highway');

Here is the corresponding interpretation using sub-parsers:

sub-parser('Numeric').subparse(_.trim).raku;

Here is a more involved example in which:

1. An LLM is asked to produce a certain set of events in JSON format

2. The JSON fragment of the result is parsed

3. The obtained list of hashes is transformed into Mermaid-JS timeline diagram

my &ft = llm-function(
        {"What are the $^a most significant events of $^b? Give the answer with date-event pairs in JSON format."},
        form => sub-parser('JSON'),
        llm-evaluator => llm-configuration('PaLM', max-tokens => 500));

my @ftRes = |&ft(9, 'WWI');
@ftRes = @ftRes.grep({ $_ !~~ Str });

my @timeline = ['timeline', 'title WW1 events'];
for @ftRes -> $record {
    @timeline.append( "{$record<date>} : {$record<event>}");
}
@timeline.join("\n\t")

References

Articles

[AA1] Anton Antonov, "LLM::Functions", (2023), RakuForPrediction at WordPress.

Packages

[AAp1] Anton Antonov, LLM::Functions Raku package, (2023), GitHub/antononcube.

[AAp2] Anton Antonov, WWW::OpenAI Raku package, (2023), GitHub/antononcube.

[AAp3] Anton Antonov, WWW::PaLM Raku package, (2023), GitHub/antononcube.