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131 lines
4.3 KiB
JavaScript
131 lines
4.3 KiB
JavaScript
import path from 'path'
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import fs from 'fs'
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import { composeFromPattern } from '@nlpjs/utils'
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import { LogHelper } from '@/helpers/log-helper'
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import { StringHelper } from '@/helpers/string-helper'
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import { SKILL_DOMAIN } from '@/helpers/skill-domain'
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/**
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* Train skills actions
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*/
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export default (lang, nlp) =>
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new Promise(async (resolve) => {
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LogHelper.title('Skills actions training')
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const supportedActionTypes = ['dialog', 'logic']
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const skillDomains = await SKILL_DOMAIN.getSkillDomains()
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for (const [domainName, currentDomain] of skillDomains) {
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const skillKeys = Object.keys(currentDomain.skills)
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LogHelper.info(`[${lang}] Training "${domainName}" domain model...`)
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for (let j = 0; j < skillKeys.length; j += 1) {
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const { name: skillName } = currentDomain.skills[skillKeys[j]]
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const currentSkill = currentDomain.skills[skillKeys[j]]
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LogHelper.info(`[${lang}] Using "${skillKeys[j]}" skill config data`)
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const configFilePath = path.join(
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currentSkill.path,
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'config',
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`${lang}.json`
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)
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if (fs.existsSync(configFilePath)) {
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const { actions, variables } = await SKILL_DOMAIN.getSkillConfig(
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configFilePath,
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lang
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)
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const actionsKeys = Object.keys(actions)
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for (let k = 0; k < actionsKeys.length; k += 1) {
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const actionName = actionsKeys[k]
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const actionObj = actions[actionName]
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const intent = `${skillName}.${actionName}`
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const {
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utterance_samples: utteranceSamples,
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answers,
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slots
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} = actionObj
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if (
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!actionObj.type ||
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!supportedActionTypes.includes(actionObj.type)
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) {
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LogHelper.error(
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`This action type isn't supported: ${actionObj.type}`
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)
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process.exit(1)
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}
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nlp.assignDomain(lang, intent, currentDomain.name)
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if (slots) {
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for (let l = 0; l < slots.length; l += 1) {
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const slotObj = slots[l]
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/**
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* TODO: handle entity within questions such as "Where does {{ hero }} live?"
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* https://github.com/axa-group/nlp.js/issues/328
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* https://github.com/axa-group/nlp.js/issues/291
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* https://github.com/axa-group/nlp.js/issues/307
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*/
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if (slotObj.item.type === 'entity') {
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nlp.slotManager.addSlot(
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intent,
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`${slotObj.name}#${slotObj.item.name}`,
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true,
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{ [lang]: slotObj.questions }
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)
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}
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/* nlp.slotManager
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.addSlot(intent, 'boolean', true, { [lang]: 'How many players?' }) */
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}
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}
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for (let l = 0; l < utteranceSamples?.length; l += 1) {
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const utterance = utteranceSamples[l]
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// Achieve Cartesian training
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const utteranceAlternatives = composeFromPattern(utterance)
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utteranceAlternatives.forEach((utteranceAlternative) => {
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nlp.addDocument(lang, utteranceAlternative, intent)
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})
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}
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// Train NLG if the action has a dialog type
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if (actionObj.type === 'dialog') {
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const variablesObj = {}
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// Dynamic variables binding if any variable is declared
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if (variables) {
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const variableKeys = Object.keys(variables)
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for (let l = 0; l < variableKeys.length; l += 1) {
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const key = variableKeys[l]
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variablesObj[`%${key}%`] = variables[variableKeys[l]]
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}
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}
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for (let l = 0; l < answers?.length; l += 1) {
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const variableKeys = Object.keys(variablesObj)
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if (variableKeys.length > 0) {
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answers[l] = StringHelper.findAndMap(answers[l], variablesObj)
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}
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nlp.addAnswer(lang, `${skillName}.${actionName}`, answers[l])
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}
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}
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}
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}
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}
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LogHelper.success(`[${lang}] "${domainName}" domain trained`)
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}
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resolve()
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})
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