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node-red-contrib-chatbot

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REDBot a Chat bot for a full featured chat bot for Telegram, Facebook Messenger and Slack. Almost no coding skills required

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const _ = require('underscore'); const { NlpManager } = require('node-nlp'); const lcd = require('../lib/helpers/lcd'); const RegisterType = require('../lib/node-installer'); const { extractValue } = require('../lib/helpers/utils'); const GlobalContextHelper = require('../lib/helpers/global-context-helper'); module.exports = function(RED) { const registerType = RegisterType(RED); const globalContextHelper = GlobalContextHelper(RED); function ChatBotNLPjs(config) { RED.nodes.createNode(this, config); const node = this; globalContextHelper.init(this.context().global); this.name = config.name; this.debug = config.debug; this.on('input', async function(msg, send, done) { // send/done compatibility for node-red < 1.0 send = send || function() { node.send.apply(node, arguments) }; done = done || function(error) { node.error.call(node, error, msg) }; const name = extractValue('string', 'name', node, msg, false); const debug = extractValue('boolean', 'debug', node, msg, false); // DOCS // entities // https://github.com/axa-group/nlp.js/blob/master/docs/v3/slot-filling.md#entities-with-the-same-name const { payload } = msg; // collect all languages from payload const languages = _.uniq([...Object.keys(payload.intents || {}), ...Object.keys(payload.entities || {})]); const manager = new NlpManager({ languages, nlu: { log: false }, autoSave: false, autoLoad: false, forceNER: true }); if (debug) { // eslint-disable-next-line no-console console.log(lcd.white('[NLP] ') + lcd.grey('Training model ') + lcd.green(name)); } // adding intents if (_.isObject(payload.intents)) { Object.keys(payload.intents).forEach(language => { Object.keys(payload.intents[language] || {}).forEach(intent => { (payload.intents[language][intent] || []).forEach(utterance => { if (debug) { // eslint-disable-next-line no-console console.log(' Intent: ' + lcd.white(intent) + ' [' + language.toUpperCase() + '] ' + lcd.green(utterance)); } manager.addDocument(language, utterance, intent); }); }); }); } // adding entities if (_.isObject(payload.entities)) { Object.keys(payload.entities).forEach(language => { Object.keys(payload.entities[language] || {}).forEach(name => { const entity = payload.entities[language][name]; if (entity.type === 'enum') { (entity.entities || []).forEach(item => { // prevent aliases containing a single empty string const aliases = (item.aliases || []).filter(str => !_.isEmpty(str)); if (debug) { // eslint-disable-next-line no-console console.log( ' Entity: ' + lcd.white(name) + ' [' + language.toUpperCase() + '] ' + lcd.green(item.name) + (_.isArray(aliases) && !_.isEmpty(aliases) ? ` (${aliases.join(',')})` : '') ); } manager.addNamedEntityText(name, item.name, [language], !_.isEmpty(aliases) ? [item.name, ...aliases] : [item.name]); }); } else if (entity.type === 'regex') { manager.nlp.addNerRegexRule(language, name, entity.regex); if (debug) { // eslint-disable-next-line no-console console.log( ' Entity: ' + lcd.white(name) + ' [' + language.toUpperCase() + '] ' + lcd.green(entity.regex) ); } } }); }); } await manager.train(); manager.save(); // store globally globalContextHelper.set('nlp_' + (!_.isEmpty(name) ? name : 'default'), manager); send({...msg, payload: manager }); done(); }); } registerType('chatbot-nlpjs-train', ChatBotNLPjs); };