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ngram-natural-language-generator

0.5.2 • Public • Published

NPM version Build Status Dependency Status

ngram-natural-language-generator

Takes in text/file(s)/stream(s) and generates random sentences that sound like they could have been in the original text using a bigram generator. Surprisingly works on most languages and writing styles.

You can experiment with your own texts here http://cesine.github.io/ngram-natural-language-generator/samples

screen shot 2015-12-07 at 1 28 34 am screen shot 2015-12-07 at 9 09 01 pm

Usage

Commandline

$ npm install ngram-natural-language-generator --save
$ ./index.js samples/jaberwocky.txt

Browser

$ bower install ngram-natural-language-generator --save

There is an example browser use in samples/index.html.

<textarea id="ngram-nlg-text"></textarea>
<textarea id="ngram-nlg-result"></textarea>
 
<script>
    window.NLG = window.exports = window.exports || {};
</script> 
 
<script src="bower_components/ngram-natural-language-generator/lib/tokenizer.js"></script>
<script src="bower_components/ngram-natural-language-generator/lib/nlg.js"></script>
<script src="bower_components/ngram-natural-language-generator/lib/ngrams.js"></script>
<script src="bower_components/ngram-natural-language-generator/lib/ngram-nlg.js"></script>
<script src="bower_components/ngram-natural-language-generator/lib/drag-and-drop-file-upload.js"></script>
 
<script>
    NLG.currentOptions  = {
        text: ''
    };
    NLG.currentOptions.text = document.getElementById('ngram-nlg-text').value;
    NLG.build(NLG.currentOptions, function(err, result){
        if (err) return console.warn(err);
        document.getElementById('ngram-nlg-result').value = NLG.generate(NLG.currentOptions.model);
    });
</script> 
 

Node

From file:

var generator = require('ngram-natural-language-generator').generator;
 
generator({
    filename: 'samples/jabberwocky.txt',
    model: {
        maxLength: 100,
        minLength: 50
    }
}, function(err, sentence){
    console.log(sentence);
    // One two. Callooh. Beware the borogoves And the claws that bite the Jabberwock my
    // beamish boy. One two. One two. And through the mome raths outgrabe. And stood The
    // frumious Bandersnatch. He took his joy. And the borogoves And the claws that bite the
    // wabe All mimsy were the Jabberwock with eyes of flame Came whiffling through and the
    // slithy toves Did gyre and through The Jabberwock. Twas brillig and shun The Jabberwock
    // my son. Beware the borogoves And the mome raths outgrabe. Beware the Jabberwock. Come
    // to my son.
});

From text:

var generator = require('ngram-natural-language-generator').generator;
 
generator({
    text: 'Colorless green ideas sleep furiously.',
    model: {
        maxLength: 100,
        minLength: 50
    }
}, function(err, sentence){
    console.log(sentence);
});

From web url:

var generator = require('ngram-natural-language-generator').generator;
var http = require('http');
 
http.get('http://www.jabberwocky.com/carroll/jabber/jabberwocky.html', function(res) {
    generator({
        stream: res
    }, function(err, sentence){
        console.log(sentence);
    });
});
 

From tokens:

If you're working with a language which doesn't tokenize on whitespace or unicode punctionation you can supply the tokens.

var generator = require('ngram-natural-language-generator').generator;
 
generator({
    tokens: ['その', '酩酊', '状態を', '愛する', 'ことに', 'よって'],
    model: {
        maxLength: 100,
        minLength: 50
    }
}, function(err, sentence){
    console.log(sentence);
});

install

npm i ngram-natural-language-generator

Downloadsweekly downloads

8

version

0.5.2

license

MIT

last publish

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