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