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NLP Manager

The NLP Manager is able to manage several languages. For each one, he manages the Named Entities, and is able to train the NLP classifier. Once we have it trained, we can ask the NLP manager to process one utterance. We can even don't tell the language and the NLP Manger will guess it from the languages that it knows. When the utterance is processed, the NLP manager will:

  • Identify the language
  • Classify the utterance using ML, and returns the classifications and the best intent and score
  • Gets the entities from the utterance. If the NLP was trained using entities in the format %entity%, then the search for entities will be limited to those that are present in this intent; otherwise, all the possible entities will be checked.
  • Gets the sentiment analysis.
const { NlpManager } = require('node-nlp');

const manager = new NlpManager({ languages: ['en'] });
manager.addNamedEntityText(
  'hero',
  'spiderman',
  ['en'],
  ['Spiderman', 'Spider-man'],
);
manager.addNamedEntityText(
  'hero',
  'iron man',
  ['en'],
  ['iron man', 'iron-man'],
);
manager.addNamedEntityText('hero', 'thor', ['en'], ['Thor']);
manager.addNamedEntityText(
  'food',
  'burguer',
  ['en'],
  ['Burguer', 'Hamburguer'],
);
manager.addNamedEntityText('food', 'pizza', ['en'], ['pizza']);
manager.addNamedEntityText('food', 'pasta', ['en'], ['Pasta', 'spaghetti']);
manager.addDocument('en', 'I saw %hero% eating %food%', 'sawhero');
manager.addDocument(
  'en',
  'I have seen %hero%, he was eating %food%',
  'sawhero',
);
manager.addDocument('en', 'I want to eat %food%', 'wanteat');
manager.train();
manager.process(
  'I saw spiderman eating spaghetti today in the city!',
).then(result => console.log(result));
// { locale: 'en',
//   localeIso2: 'en',
//   language: 'English',
//   utterance: 'I saw spiderman eating spaghetti today in the city!',
//   classification:
//    [ { label: 'sawhero', value: 0.9920519933583061 },
//      { label: 'wanteat', value: 0.00794800664169383 } ],
//   intent: 'sawhero',
//   score: 0.9920519933583061,
//   entities:
//    [ { start: 6,
//        end: 15,
//        levenshtein: 0,
//        accuracy: 1,
//        option: 'spiderman',
//        sourceText: 'Spiderman',
//        entity: 'hero',
//        utteranceText: 'spiderman' },
//      { start: 23,
//        end: 32,
//        levenshtein: 0,
//        accuracy: 1,
//        option: 'pasta',
//        sourceText: 'spaghetti',
//        entity: 'food',
//        utteranceText: 'spaghetti' } ],
//   sentiment:
//    { score: 0.708,
//      comparative: 0.07866666666666666,
//      vote: 'positive',
//      numWords: 9,
//      numHits: 2,
//      type: 'senticon',
//      language: 'en' } }

Also, you can save and load the NLP Manager to be reused without having to train it, because the thetas of the ML are also stored.

      manager.train();
      manager.save(filename);
      manager = new NlpManager();
      manager.load(filename);
      manager
        .process('I saw spiderman eating spaghetti today in the city!')
        .then(result => {});

If no filename is provided by default it is './model.nlp'.

Transformers

You could pass transformer function to NLPManager constructor, which might be used to modify process output format.

const manager = new NlpManager({
 transformer: (originalProcessOutput) => {
   // put some modifications logic (it might be async)
   // and return modified value
   return Promise.resolve({ modified: 'VALUE' });
 }
});