/*****************************************************************************\
| ( )_ _ |
| _ _ _ __ _ _ __ ___ ___ _ _ | ,_)(_) ___ ___ _ |
| ( '_`\ ( '__)/'_` ) /'_ `\/' _ ` _ `\ /'_` )| | | |/',__)/' _ `\ /'_`\ |
| | (_) )| | ( (_| |( (_) || ( ) ( ) |( (_| || |_ | |\__, \| ( ) |( (_) ) |
| | ,__/'(_) `\__,_)`\__ |(_) (_) (_)`\__,_)`\__)(_)(____/(_) (_)`\___/' |
| | | ( )_) | |
| (_) \___/' |
| |
| General Bots Copyright (c) Pragmatismo.io. All rights reserved. |
| Licensed under the AGPL-3.0. |
| |
| According to our dual licensing model, this program can be used either |
| under the terms of the GNU Affero General Public License, version 3, |
| or under a proprietary license. |
| |
| The texts of the GNU Affero General Public License with an additional |
| permission and of our proprietary license can be found at and |
| in the LICENSE file you have received along with this program. |
| |
| This program is distributed in the hope that it will be useful, |
| but WITHOUT ANY WARRANTY, without even the implied warranty of |
| MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
| GNU Affero General Public License for more details. |
| |
| "General Bots" is a registered trademark of Pragmatismo.io. |
| The licensing of the program under the AGPLv3 does not imply a |
| trademark license. Therefore any rights, title and interest in |
| our trademarks remain entirely with us. |
| |
\*****************************************************************************/
"use strict"
import { IGBDialog } from "botlib"
import { AzureText } from "pragmatismo-io-framework"
import { GBMinInstance } from "botlib"
import { KBService } from './../services/KBService'
import { BotAdapter } from "botbuilder"
import { LuisRecognizer } from "botbuilder-ai"
const logger = require("../../../src/logger")
export class AskDialog extends IGBDialog {
/**
* Setup dialogs flows and define services call.
*
* @param bot The bot adapter.
* @param min The minimal bot instance data.
*/
static setup(bot: BotAdapter, min: GBMinInstance) {
const service = new KBService(min.core.sequelize)
const model = new LuisRecognizer({
appId: min.instance.nlpAppId,
subscriptionKey: min.instance.nlpSubscriptionKey,
serviceEndpoint: min.instance.nlpServerUrl
})
min.dialogs.add("/answer", [
async (dc, args) => {
// Initialize values.
const user = min.userState.get(dc.context)
let text = args.query
if (!text) {
throw new Error(`/answer being called with no args.query text.`)
}
let locale = await AzureText.getLocale(min.instance.textAnalyticsKey,
min.instance.textAnalyticsServerUrl, text)
if (locale != dc.context.activity.locale.split("-")[0])
{
switch(locale)
{
case "pt":
await dc.context.sendActivity("OK, mundando de idioma para o Português...")
dc.context.activity.locale = "pt-BR"
break
case "en":
await dc.context.sendActivity("OK, changing language to English...")
dc.context.activity.locale = "en-US"
break
default:
await dc.context.sendActivity(`Unknown language: ${locale}`)
break
}
}
// Stops any content on projector.
await min.conversationalService.sendEvent(dc, "stop", null)
// Handle extra text from FAQ.
if (args && args.query) {
text = args.query
} else if (args && args.fromFaq) {
let messages = [
`Ótima escolha, procurando resposta para sua questão...`,
`Pesquisando sobre o termo...`,
`Aguarde, por favor, enquanto acho sua resposta...`
]
await dc.context.sendActivity(messages[0]) // TODO: Handle rnd.
}
// Spells check the input text before sending Search or NLP.
if (min.instance.spellcheckerKey) {
let data = await AzureText.getSpelledText(
min.instance.spellcheckerKey,
text)
if (data != text) {
logger.info(`Spelling corrected: ${data}`)
text = data
}
}
// Searches KB for the first time.
user.lastQuestion = text
let resultsA = await service.ask(
min.instance,
text,
min.instance.searchScore,
user.subjects)
// If there is some result, answer immediately.
if (resultsA && resultsA.answer) {
// Saves some context info.
user.isAsking = false
user.lastQuestionId = resultsA.questionId
// Sends the answer to all outputs, including projector.
await service.sendAnswer(min.conversationalService, dc, resultsA.answer)
// Goes to ask loop, again.
await dc.replace("/ask", { isReturning: true })
} else {
// Second time running Search, now with no filter.
let resultsB = await service.ask(min.instance, text,
min.instance.searchScore, null)
// If there is some result, answer immediately.
if (resultsB && resultsB.answer) {
// Saves some context info.
const user = min.userState.get(dc.context)
user.isAsking = false
user.lastQuestionId = resultsB.questionId
// Informs user that a broader search will be used.
if (user.subjects.length > 0) {
let subjectText =
`${KBService.getSubjectItemsSeparatedBySpaces(
user.subjects
)}`
let messages = [
`Respondendo nao apenas sobre ${subjectText}... `,
`Respondendo de modo mais abrangente...`,
`Vou te responder de modo mais abrangente...
Não apenas sobre ${subjectText}`
]
await dc.context.sendActivity(messages[0]) // TODO: Handle rnd.
}
// Sends the answer to all outputs, including projector.
await service.sendAnswer(min.conversationalService, dc, resultsB.answer)
await dc.replace("/ask", { isReturning: true })
} else {
let data = await min.conversationalService.runNLP(dc, min, text)
if (!data) {
let messages = [
"Desculpe-me, não encontrei nada a respeito.",
"Lamento... Não encontrei nada sobre isso. Vamos tentar novamente?",
"Desculpe-me, não achei nada parecido. Poderia tentar escrever de outra forma?"
]
await dc.context.sendActivity(messages[0]) // TODO: Handle rnd.
await dc.replace("/ask", { isReturning: true })
}
}
}
}
])
min.dialogs.add("/ask", [
async (dc, args) => {
const user = min.userState.get(dc.context)
user.isAsking = true
if (!user.subjects) {
user.subjects = []
}
let text = []
if (user.subjects.length > 0) {
text = [
`Faça sua pergunta...`,
`Pode perguntar sobre o assunto em questão... `,
`Qual a pergunta?`
]
}
if (args && args.isReturning) {
text = [
"Sobre o que mais posso ajudar?",
"Então, posso ajudar em algo a mais?",
"Deseja fazer outra pergunta?"
]
}
if (text.length > 0) {
await dc.prompt('textPrompt', text[0])
}
},
async (dc, value) => {
await dc.endAll()
await dc.begin("/answer", { query: value })
}
])
}
}