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).
53 lines
No EOL
1.9 KiB
JavaScript
53 lines
No EOL
1.9 KiB
JavaScript
import axios from 'axios';
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import { logger } from '../../utils/logger.js';
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export async function summarizeTicketWithGrokFromContext(context, ticketId) {
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const systemPrompt = `
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You are an expert HVAC/facilities technician and ServiceChannel ticket analyst.
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Summarize this ticket clearly and concisely.
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Use the **ticket description** as the primary source for the **main problem / reason for the ticket**.
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Use the notes to provide timeline, actions, status updates, and pending items.
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Structure your summary with these sections:
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- **Main Problem** (from description)
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- **Key Events & Timeline** (chronological bullets from notes, most recent last)
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- **Actions Taken**
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- **Current Status / Blockers**
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- **Pending / Next Steps**
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Keep it professional, neutral, factual, under 250 words.
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Use bullet points where helpful.
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If notes are repetitive, deduplicate them.
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If no notes, omit "Key Events & Timeline" or say "No notes recorded."
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`;
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const userPrompt = `Summarize this ServiceChannel ticket:\n${context}`;
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try {
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const response = await axios.post(
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process.env.XAI_URL,
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{
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model: process.env.XAI_MODEL, // or your working model
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messages: [
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{ role: 'system', content: systemPrompt },
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{ role: 'user', content: userPrompt }
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],
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temperature: 0.3,
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max_tokens: 500
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},
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{
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headers: {
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Authorization: `Bearer ${process.env.XAI_API_KEY}`,
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'Content-Type': 'application/json'
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}
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}
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);
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return response.data.choices[0].message.content.trim();
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} catch (err) {
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logger('xai:client', `Error: ${err.response?.data || err.message}`, 'error');
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return `(Summary failed) Raw ticket info: ${context.substring(0, 200)}...`;
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}
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} |