226 lines
8.2 KiB
TypeScript
226 lines
8.2 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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"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 { Messages } from "../strings";
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import { WaterfallDialog } from "botbuilder-dialogs";
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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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min.dialogs.add(new WaterfallDialog("/answerEvent", [
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async step => {
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if (step.options && step.options["questionId"]) {
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let question = await service.getQuestionById(
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min.instance.instanceId,
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step.options["questionId"]
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);
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let answer = await service.getAnswerById(
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min.instance.instanceId,
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question.answerId
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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, step, answer);
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await step.replaceDialog("/ask", { isReturning: true });
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}
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return await step.next();
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}
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]));
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min.dialogs.add(new WaterfallDialog("/answer", [
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async step => {
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const user = await min.userProfile.get(step.context, {});
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let text = step.options["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 = step.context.activity.locale;
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// Stops any content on projector.
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await min.conversationalService.sendEvent(step, "stop", null);
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// Handle extra text from FAQ.
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if (step.options && step.options["query"]) {
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text = step.options["query"];
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} else if (step.options && step.options["fromFaq"]) {
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await step.context.sendActivity(Messages[locale].going_answer);
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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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);
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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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await min.userProfile.set(step.context, user);
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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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);
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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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await min.userProfile.set(step.context, user);
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// Sends the answer to all outputs, including projector.
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await service.sendAnswer(
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min.conversationalService,
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step,
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resultsA.answer
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);
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// Goes to ask loop, again.
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await step.replaceDialog("/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(
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min.instance,
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text,
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min.instance.searchScore,
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null
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);
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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 = await min.userProfile.get(step.context, {});
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user.isAsking = false;
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user.lastQuestionId = resultsB.questionId;
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await min.userProfile.set(step.context, user);
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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 = `${KBService.getSubjectItemsSeparatedBySpaces(
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user.subjects
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)}`;
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await step.context.sendActivity(Messages[locale].wider_answer);
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}
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// Sends the answer to all outputs, including projector.
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await service.sendAnswer(
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min.conversationalService,
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step,
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resultsB.answer
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);
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await step.replaceDialog("/ask", { isReturning: true });
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} else {
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if (!(await min.conversationalService.routeNLP(step, min, text))) {
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await step.context.sendActivity(Messages[locale].did_not_find);
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await step.replaceDialog("/ask", { isReturning: true });
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}
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}
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}
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return await step.next();
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}
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]));
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min.dialogs.add(new WaterfallDialog("/ask", [
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async step => {
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const locale = step.context.activity.locale;
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const user = await min.userProfile.get(step.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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// Three forms of asking.
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if (step.options && step.options["firstTime"]) {
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text = Messages[locale].ask_first_time;
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} else if (step.options && step.options["isReturning"]) {
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text = Messages[locale].anything_else;
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} else if (user.subjects.length > 0) {
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text = Messages[locale].which_question;
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} else {
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throw new Error("Invalid use of /ask");
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}
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if (text.length > 0) {
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await step.prompt("textPrompt", text);
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}
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return await step.next();
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},
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async step => {
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await step.replaceDialog("/answer", { query: step.result });
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return await step.next();
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}
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]));
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}
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}
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