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412 lines
10 KiB
TypeScript
412 lines
10 KiB
TypeScript
/* eslint-disable new-cap */
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import type { ConversationData } from '@rocket.chat/core-services';
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import type { IOmnichannelRoom } from '@rocket.chat/core-typings';
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import type { ILivechatRoomsModel } from '@rocket.chat/model-typings';
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import type moment from 'moment';
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import type { Filter } from 'mongodb';
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import { secondsToHHMMSS } from '../../../lib/utils/secondsToHHMMSS';
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type AgentOverviewValidActions =
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| 'Total_conversations'
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| 'Avg_chat_duration'
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| 'Total_messages'
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| 'Avg_first_response_time'
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| 'Best_first_response_time'
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| 'Avg_response_time'
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| 'Avg_reaction_time';
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export class AgentOverviewData {
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constructor(private readonly roomsModel: ILivechatRoomsModel) {}
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updateMap<K>(map: Map<K, number>, key: K, value: number) {
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const currentKeyValue = map.get(key);
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map.set(key, currentKeyValue ? currentKeyValue + value : value);
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}
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sortByValue(data: { value: string }[], inv = false) {
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data.sort((a, b) => {
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// sort array
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if (parseFloat(a.value) > parseFloat(b.value)) {
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return inv ? -1 : 1; // if inv, reverse sort
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}
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if (parseFloat(a.value) < parseFloat(b.value)) {
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return inv ? 1 : -1;
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}
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return 0;
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});
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}
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isActionAllowed(action: string | undefined): action is AgentOverviewValidActions {
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if (!action) {
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return false;
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}
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return [
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'Total_conversations',
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'Avg_chat_duration',
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'Total_messages',
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'Avg_first_response_time',
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'Best_first_response_time',
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'Avg_response_time',
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'Avg_reaction_time',
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].includes(action);
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}
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callAction<T extends AgentOverviewValidActions>(action: T, ...args: [moment.Moment, moment.Moment, string?, Filter<IOmnichannelRoom>?]) {
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switch (action) {
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case 'Total_conversations':
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return this.Total_conversations(...args);
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case 'Avg_chat_duration':
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return this.Avg_chat_duration(...args);
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case 'Total_messages':
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return this.Total_messages(...args);
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case 'Avg_first_response_time':
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return this.Avg_first_response_time(...args);
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case 'Best_first_response_time':
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return this.Best_first_response_time(...args);
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case 'Avg_response_time':
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return this.Avg_response_time(...args);
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case 'Avg_reaction_time':
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return this.Avg_reaction_time(...args);
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default:
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throw new Error('Invalid action');
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}
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}
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async Total_conversations(from: moment.Moment, to: moment.Moment, departmentId?: string, extraQuery: Filter<IOmnichannelRoom> = {}) {
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let total = 0;
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const agentConversations = new Map(); // stores total conversations for each agent
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const date = {
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gte: from.toDate(),
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lte: to.toDate(),
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};
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const data: ConversationData = {
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head: [
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{
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name: 'Agent',
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},
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{
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name: '%_of_conversations',
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},
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],
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data: [],
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};
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await this.roomsModel
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.getAnalyticsMetricsBetweenDateWithMessages(
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'l',
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date,
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{
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departmentId,
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},
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{},
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extraQuery,
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)
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.forEach((room) => {
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if (room.servedBy) {
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this.updateMap(agentConversations, room.servedBy.username, 1);
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total++;
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}
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});
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agentConversations.forEach((value, key) => {
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// calculate percentage
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const percentage = ((value / total) * 100).toFixed(2);
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data.data.push({
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name: key,
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value: `${percentage}%`,
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});
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});
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this.sortByValue(data.data, true); // reverse sort array
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return data;
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}
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async Avg_chat_duration(from: moment.Moment, to: moment.Moment, departmentId?: string, extraQuery: Filter<IOmnichannelRoom> = {}) {
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const agentChatDurations = new Map(); // stores total conversations for each agent
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const date = {
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gte: from.toDate(),
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lte: to.toDate(),
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};
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const data: ConversationData = {
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head: [
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{
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name: 'Agent',
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},
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{
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name: 'Avg_chat_duration',
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},
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],
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data: [],
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};
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await this.roomsModel.getAnalyticsMetricsBetweenDate('l', date, { departmentId }, extraQuery).forEach(({ metrics, servedBy }) => {
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if (servedBy && metrics && metrics.chatDuration) {
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if (agentChatDurations.has(servedBy.username)) {
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agentChatDurations.set(servedBy.username, {
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chatDuration: agentChatDurations.get(servedBy.username).chatDuration + metrics.chatDuration,
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total: agentChatDurations.get(servedBy.username).total + 1,
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});
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} else {
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agentChatDurations.set(servedBy.username, {
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chatDuration: metrics.chatDuration,
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total: 1,
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});
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}
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}
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});
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agentChatDurations.forEach((obj, key) => {
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// calculate percentage
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const avg = (obj.chatDuration / obj.total).toFixed(2);
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data.data.push({
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name: key,
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value: secondsToHHMMSS(avg),
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});
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});
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this.sortByValue(data.data, true); // reverse sort array
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return data;
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}
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async Total_messages(from: moment.Moment, to: moment.Moment, departmentId?: string, extraQuery: Filter<IOmnichannelRoom> = {}) {
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const agentMessages = new Map(); // stores total conversations for each agent
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const date = {
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gte: from.toDate(),
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lte: to.toDate(),
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};
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const data: ConversationData = {
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head: [
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{
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name: 'Agent',
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},
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{
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name: 'Total_messages',
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},
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],
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data: [],
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};
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// we don't want to count visitor messages
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const extraFilter = { $lte: ['$token', null] };
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await this.roomsModel
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.getAnalyticsMetricsBetweenDateWithMessages('l', date, { departmentId }, extraFilter, extraQuery)
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.forEach(({ servedBy, msgs }) => {
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if (servedBy) {
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this.updateMap(agentMessages, servedBy.username, msgs);
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}
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});
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agentMessages.forEach((value, key) => {
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// calculate percentage
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data.data.push({
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name: key,
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value,
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});
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});
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this.sortByValue(data.data, true); // reverse sort array
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return data;
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}
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async Avg_first_response_time(from: moment.Moment, to: moment.Moment, departmentId?: string, extraQuery: Filter<IOmnichannelRoom> = {}) {
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const agentAvgRespTime = new Map(); // stores avg response time for each agent
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const date = {
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gte: from.toDate(),
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lte: to.toDate(),
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};
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const data: ConversationData = {
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head: [
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{
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name: 'Agent',
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},
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{
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name: 'Avg_first_response_time',
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},
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],
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data: [],
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};
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await this.roomsModel.getAnalyticsMetricsBetweenDate('l', date, { departmentId }, extraQuery).forEach(({ metrics, responseBy }) => {
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if (responseBy && metrics && metrics.response && metrics.response.ft) {
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if (agentAvgRespTime.has(responseBy.username)) {
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agentAvgRespTime.set(responseBy.username, {
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frt: agentAvgRespTime.get(responseBy.username).frt + metrics.response.ft,
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total: agentAvgRespTime.get(responseBy.username).total + 1,
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});
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} else {
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agentAvgRespTime.set(responseBy.username, {
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frt: metrics.response.ft,
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total: 1,
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});
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}
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}
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});
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agentAvgRespTime.forEach((obj, key) => {
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// calculate avg
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const avg = obj.frt / obj.total;
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data.data.push({
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name: key,
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value: secondsToHHMMSS(avg.toFixed(2)),
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});
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});
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this.sortByValue(data.data, false); // sort array
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return data;
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}
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async Best_first_response_time(from: moment.Moment, to: moment.Moment, departmentId?: string, extraQuery: Filter<IOmnichannelRoom> = {}) {
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const agentFirstRespTime = new Map(); // stores best response time for each agent
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const date = {
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gte: from.toDate(),
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lte: to.toDate(),
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};
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const data: ConversationData = {
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head: [
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{
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name: 'Agent',
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},
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{
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name: 'Best_first_response_time',
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},
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],
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data: [],
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};
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await this.roomsModel.getAnalyticsMetricsBetweenDate('l', date, { departmentId }, extraQuery).forEach(({ metrics, responseBy }) => {
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if (responseBy && metrics && metrics.response && metrics.response.ft) {
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if (agentFirstRespTime.has(responseBy.username)) {
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agentFirstRespTime.set(responseBy.username, Math.min(agentFirstRespTime.get(responseBy.username), metrics.response.ft));
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} else {
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agentFirstRespTime.set(responseBy.username, metrics.response.ft);
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}
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}
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});
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agentFirstRespTime.forEach((value, key) => {
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// calculate avg
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data.data.push({
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name: key,
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value: secondsToHHMMSS(value.toFixed(2)),
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});
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});
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this.sortByValue(data.data, false); // sort array
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return data;
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}
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async Avg_response_time(from: moment.Moment, to: moment.Moment, departmentId?: string, extraQuery: Filter<IOmnichannelRoom> = {}) {
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const agentAvgRespTime = new Map(); // stores avg response time for each agent
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const date = {
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gte: from.toDate(),
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lte: to.toDate(),
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};
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const data: ConversationData = {
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head: [
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{
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name: 'Agent',
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},
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{
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name: 'Avg_response_time',
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},
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],
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data: [],
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};
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await this.roomsModel.getAnalyticsMetricsBetweenDate('l', date, { departmentId }, extraQuery).forEach(({ metrics, servedBy }) => {
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if (servedBy && metrics && metrics.response && metrics.response.avg) {
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if (agentAvgRespTime.has(servedBy.username)) {
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agentAvgRespTime.set(servedBy.username, {
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avg: agentAvgRespTime.get(servedBy.username).avg + metrics.response.avg,
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total: agentAvgRespTime.get(servedBy.username).total + 1,
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});
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} else {
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agentAvgRespTime.set(servedBy.username, {
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avg: metrics.response.avg,
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total: 1,
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});
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}
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}
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});
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agentAvgRespTime.forEach((obj, key) => {
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// calculate avg
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const avg = obj.avg / obj.total;
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data.data.push({
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name: key,
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value: secondsToHHMMSS(avg.toFixed(2)),
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});
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});
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this.sortByValue(data.data, false); // sort array
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return data;
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}
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async Avg_reaction_time(from: moment.Moment, to: moment.Moment, departmentId?: string, extraQuery: Filter<IOmnichannelRoom> = {}) {
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const agentAvgReactionTime = new Map(); // stores avg reaction time for each agent
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const date = {
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gte: from.toDate(),
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lte: to.toDate(),
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};
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const data: ConversationData = {
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head: [
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{
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name: 'Agent',
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},
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{
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name: 'Avg_reaction_time',
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},
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],
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data: [],
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};
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await this.roomsModel.getAnalyticsMetricsBetweenDate('l', date, { departmentId }, extraQuery).forEach(({ metrics, servedBy }) => {
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if (servedBy && metrics && metrics.reaction && metrics.reaction.ft) {
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if (agentAvgReactionTime.has(servedBy.username)) {
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agentAvgReactionTime.set(servedBy.username, {
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frt: agentAvgReactionTime.get(servedBy.username).frt + metrics.reaction.ft,
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total: agentAvgReactionTime.get(servedBy.username).total + 1,
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});
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} else {
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agentAvgReactionTime.set(servedBy.username, {
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frt: metrics.reaction.ft,
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total: 1,
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});
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}
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}
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});
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agentAvgReactionTime.forEach((obj, key) => {
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// calculate avg
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const avg = obj.frt / obj.total;
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data.data.push({
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name: key,
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value: secondsToHHMMSS(avg.toFixed(2)),
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});
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});
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this.sortByValue(data.data, false); // sort array
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return data;
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}
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}
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