jmcqueen
351f89a9a4
Multi-integration Webex chat/HTTP bot that unifies phone, AV, and network status for retail store support. Consolidates data from Webex Calling, Meraki, Workspace ONE (MDM), Atlas AMP, RED digital signage, and OptiSigns into rich per-store status commands. Key surfaces: - /phonestatus, /avstatus — per-store phone & AV device reports with clickable Meraki deep-links and per-port detail. - /webexhost — check/assign Webex Meetings host licenses via the Service App; adaptive-card confirmation flow, HTTP-API-gated. - /offboarduser — full Webex Admin offboarding (auth revoke, device wipe, license removal); adaptive-card confirmation. - /jirapoll — on-demand trigger for the hourly Jira poller. - /bulkavstatuscsv — bulk store CSV export with concurrency limits. Automation: - Hourly Jira poller (node-cron) with an X.AI (Grok) ticket classifier that categorizes unassigned tickets as phone/av/skip, extracts store numbers from free-text, and enriches Jira with the same detailed markdown the chat commands emit (converted to Jira ADF, preserves bold + Meraki links). Idempotent via a `bot-enriched` Jira label. Architecture: - Node.js 20+, ESM, Express 5, webex-node-bot-framework. - Layered integrations (integrations/*), services (services/*), commands (commands/*), utils (utils/*). - Shared markdown renderers (services/renderers/*) feed both chat handlers and the Jira poller so the two surfaces stay in sync. - Hand-rolled markdown-to-ADF converter (utils/markdownToAdf.js) — no new npm dependency. - Node built-in test runner (`node --test tests/*.test.js`), 30 tests covering the converter, renderers, and poller ADF assembly. Docker + docker-compose deployment. Config via .env (see .env.example for the full option surface).
100 lines
No EOL
3.2 KiB
JavaScript
100 lines
No EOL
3.2 KiB
JavaScript
// src/services/jiraSummarizer.js
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import { callGrok } from '../utils/grokClient.js';
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import { adfToPlainText } from '../utils/adfToPlainText.js';
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import { logger } from '../utils/logger.js';
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const GROK_DELAY_MS = 800;
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export async function summarizeJiraTicket(ticket) {
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const fields = ticket.fields || {};
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const key = ticket.key;
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const summary = fields.summary || '';
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const description = fields.description
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? adfToPlainText(fields.description)
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: '';
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const comments = fields.comment?.comments || [];
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let commentText = '';
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if (comments.length > 0) {
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commentText = comments.map(c => {
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const date = new Date(c.created).toLocaleDateString('en-US');
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const author = c.author?.displayName || 'Unknown';
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let body = typeof c.body === 'string' ? c.body : adfToPlainText(c.body);
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return `[${date}] ${author}:\n${body}`;
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}).join('\n\n');
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} else {
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commentText = 'No comments found in the ticket.';
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}
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const prompt = `
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You are an expert IT support analyst summarizing Jira tickets.
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**Ticket:** ${key}
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**Summary:** ${summary}
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**Description:** ${description}
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**Comments/Notes (chronological):**
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${commentText}
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Analyze the ticket and respond with **exactly** this structure. Do not add any extra text, headings, or explanations outside these sections:
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**Reported Problem:**
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Describe the original issue clearly and concisely.
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**Steps Taken:**
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List the key troubleshooting and resolution steps taken (pull heavily from comments).
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**Final Resolution:**
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State how the issue was ultimately resolved or closed. If still open, note the current status and any pending actions.
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Keep each section to 2-4 sentences maximum. Be factual and technical.
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`;
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try {
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await new Promise(resolve => setTimeout(resolve, GROK_DELAY_MS));
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const aiResponse = await callGrok(prompt, {
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temperature: 0.35,
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max_tokens: 500
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});
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return aiResponse.trim();
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} catch (err) {
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logger('jira:summarizer', `Failed for ${key}: ${err.message}`, 'error');
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return `**Reported Problem:** No details available.\n**Steps Taken:** No information recorded.\n**Final Resolution:** No resolution documented.`;
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}
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}
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export async function analyzeCommonIssues(tickets) {
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if (tickets.length < 3) return '';
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const ticketData = tickets.map(t => ({
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key: t.key,
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summary: t.fields.summary || '',
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component: t.fields.components?.[0]?.name || '',
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status: t.fields.status?.name || ''
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}));
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const prompt = `
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You are analyzing multiple Jira tickets for the same store.
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Tickets:
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${JSON.stringify(ticketData, null, 2)}
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Identify 2–4 common patterns or recurring issues across these tickets.
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Focus on technical root causes or trends (e.g., "Multiple wireless phone audio issues after firmware updates", "Frequent voicemail greeting resets", etc.).
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Respond with a short bullet-point list. Be concise and specific.
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`;
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try {
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await new Promise(resolve => setTimeout(resolve, 1200)); // extra delay for analysis
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const analysis = await callGrok(prompt, { temperature: 0.5, max_tokens: 350 });
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return analysis;
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} catch (err) {
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logger('jira:summarizer', `Analysis failed: ${err.message}`, 'error');
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return "Unable to identify common patterns at this time.";
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}
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} |