NAME
Hailo - A pluggable Markov engine analogous to MegaHAL
SYNOPSIS
This is the synopsis for using Hailo as a module. See hailo for
command-line invocation.
# Hailo requires Perl 5.10
use 5.010;
use Any::Moose;
use Hailo;
# Construct a new in-memory Hailo using the SQLite backend. See
# backend documentation for other options.
my $hailo = Hailo->new;
# Various ways to learn
my @train_this = ("I like big butts", "and I can not lie");
$hailo->learn(\@train_this);
$hailo->learn($_) for @train_this;
# Heavy-duty training interface. Backends may drop some safety
# features like journals or synchronous IO to train faster using
# this mode.
$hailo->train("megahal.trn");
$hailo->train($filehandle);
# Make the brain babble
say $hailo->reply("hello good sir.");
# Just say something at random
say $hailo->reply();
DESCRIPTION
Hailo is a fast and lightweight markov engine intended to replace
AI::MegaHAL. It has a Mouse (or Moose) based core with pluggable
storage, tokenizer and engine backends.
It is similar to MegaHAL in functionality, the main differences (with
the default backends) being better scalability, drastically less memory
usage, an improved tokenizer, and tidier output.
With this distribution, you can create, modify, and query Hailo brains.
To use Hailo in event-driven POE applications, you can use the
POE::Component::Hailo wrapper. One example is
POE::Component::IRC::Plugin::Hailo, which implements an IRC chat bot.
Etymology
*Hailo* is a portmanteau of *HAL* (as in MegaHAL) and failo
<http://identi.ca/failo>.
Backends
Hailo supports pluggable storage and tokenizer backends, it also
supports a pluggable UI backend which is used by the hailo command-line
utility.
Storage
Hailo can currently store its data in either a SQLite, PostgreSQL or
MySQL database. Some NoSQL backends were supported in earlier versions,
but they were removed as they had no redeeming quality.
SQLite is the primary target for Hailo. It's much faster and uses less
resources than the other two. It's highly recommended that you use it.
See "Comparison of backends" in Hailo::Storage for benchmarks showing
how the various backends compare under different workloads, and how you
can create your own.
Tokenizer
By default Hailo will use the word tokenizer to split up input by
whitespace, taking into account things like quotes, sentence terminators
and more.
There's also a the character tokenizer. It's not generally useful for a
conversation bot but can be used to e.g. generate new words given a list
of existing words.
UPGRADING
Hailo makes no promises about brains generated with earlier versions
being compatable with future version and due to the way Hailo works
there's no practical way to make that promise. Learning in Hailo is
lossy so an accurate conversion is impossible.
If you're maintaining a Hailo brain that you want to keep using you
should save the input you trained it on and re-train when you upgrade.
Hailo is always going to lose information present in the input you give
it. How input tokens get split up and saved to the storage backend
depends on the version of the tokenizer being used and how that input
gets saved to the database.
For instance if an earlier version of Hailo tokenized "foo+bar" simply
as "foo+bar" but a later version split that up into "foo", "+", "bar",
then an input of ""foo+bar are my favorite metasyntactic variables""
wouldn't take into account the existing "foo+bar" string in the
database.
Tokenizer changes like this would cause the brains to accumulate garbage
and would leave other parts in a state they wouldn't otherwise have
gotten into.
There have been more drastic changes to the database format itself in
the past.
Having said all that the database format and the tokenizer are
relatively stable. At the time of writing 0.33 is the latest release and
it's compatable with brains down to at least 0.17. If you're upgrading
and there isn't a big notice about the storage format being incompatable
in the Changes file your old brains will probably work just fine.
ATTRIBUTES
"brain"
The name of the brain (file name, database name) to use as storage.
There is no default. Whether this gets used at all depends on the
storage backend, currently only SQLite uses it.
"save_on_exit"
A boolean value indicating whether Hailo should save its state before
its object gets destroyed. This defaults to true and will simply call
save at "DEMOLISH" time.
See "in_memory" in Hailo::Storage::SQLite for how the SQLite backend
uses this option.
"order"
The Markov order (chain length) you want to use for an empty brain. The
default is 2.
"engine_class"
"storage_class"
"tokenizer_class"
"ui_class"
A a short name name of the class we use for the engine, storage,
tokenizer or ui backends.
By default this is Default for the engine, SQLite for storage, Words for
the tokenizer and ReadLine for the UI. The UI backend is only used by
the hailo command-line interface.
You can only specify the short name of one of the packages Hailo itself
ships with. If you need another class then just prefix the package with
a plus (Catalyst style), e.g. "+My::Foreign::Tokenizer".
"engine_args"
"storage_args"
"tokenizer_args"
"ui_args"
A "HashRef" of arguments for engine/storage/tokenizer/ui backends. See
the documentation for the backends for what sort of arguments they
accept.
METHODS
"new"
This is the constructor. It accepts the attributes specified in
"ATTRIBUTES".
"learn"
Takes a string or an array reference of strings and learns from them.
"train"
Takes a filename, filehandle or array reference and learns from all its
lines. If a filename is passed, the file is assumed to be UTF-8 encoded.
Unlike "learn", this method sacrifices some safety (disables the
database journal, fsyncs, etc) for speed while learning.
You can prove a second parameter which, if true, will use aggressive
caching while training, which will speed things up considerably for
large inputs, but will take up quite a bit of memory.
"reply"
Takes an optional line of text and generates a reply that might be
relevant.
"learn_reply"
Takes a string argument, learns from it, and generates a reply that
might be relevant. This is equivalent to calling learn followed by
reply.
"save"
Tells the underlying storage backend to save its state, any arguments to
this method will be passed as-is to the backend.
"stats"
Takes no arguments. Returns the number of tokens, expressions, previous
token links and next token links.
SUPPORT
You can join the IRC channel *#hailo* on FreeNode if you have questions.
BUGS
Bugs, feature requests and other issues are tracked in Hailo's RT on
rt.cpan.org <https://rt.cpan.org/Dist/Display.html?Name=Hailo>
SEE ALSO
* POE::Component::Hailo - A non-blocking POE wrapper around Hailo
* POE::Component::IRC::Plugin::Hailo - A Hailo IRC bot plugin
* <http://github.com/hinrik/failo> - Failo, an IRC bot that uses Hailo
* <http://github.com/bingos/gumbybrain> - GumbyBRAIN, a more famous
IRC bot that uses Hailo
* Hailo::UI::Web - A Catalyst and jQuery powered web interface to
Hailo available at hailo.nix.is <http://hailo.nix.is> and as
hailo-ui-web <http://github.com/avar/hailo-ui-web> on GitHub
<http://github.com>
* tweetmix <http://www.tweetmix.me/>, a random tweet generator powered
by Hailo
* <http://github.com/pteichman/cobe> - cobe, a Python port of MegaHAL
"inspired by the success of Hailo"
LINKS
* hailo.org <http://hailo.org> - Hailo's website
* <http://bit.ly/hailo_rewrite_of_megahal> - Hailo: A Perl rewrite of
MegaHAL, A blog posting about the motivation behind Hailo
* <http://blogs.perl.org/users/aevar_arnfjor_bjarmason/hailo/> - More
blog posts about Hailo on Ævar Arnfjörð Bjarmason's blogs.perl.org
<http://blogs.perl.org> blog
* Hailo on freshmeat <http://freshmeat.net/projects/hailo> and ohloh
<https://www.ohloh.net/p/hailo>
AUTHORS
Hinrik Örn Sigurðsson, hinrik.sig@gmail.com
Ævar Arnfjörð Bjarmason <avar@cpan.org>
LICENSE AND COPYRIGHT
Copyright 2010 Hinrik Örn Sigurðsson and Ævar Arnfjörð Bjarmason
<avar@cpan.org>
This program is free software, you can redistribute it and/or modify it
under the same terms as Perl itself.