gigafibre-fsm/services/targo-hub/lib/vision.js
louispaulb 98458861c3 feat(dispatch): capacité AM/PM, durées additives, capture terrain (/field), sync techs
Hub (lib/roster.js, vision.js, legacy-dispatch-sync.js, server.js) + Ops + pont legacy.

- Capacité par jour AM/PM (Soir = réserve garde/urgence, jamais offerte) calculée
  client-side sur les techs visibles -> suit le filtre de compétence.
- Modèle de durée ADDITIF (caractéristiques, tableur inline) + auto-détection
  DÉTERMINISTE par mots-clés (sans IA permanente) ; est_min branché sur capacité + pool.
- Capture terrain passive : endpoints publics /field (job/tech/checkpoint/ts/photo/
  device/vision), tokens HMAC signés sans PII ; dérive actual_start/end. UI hébergée
  public/field-app.html (liste/carte Mapbox/Street View/photo/scan MLKit->Gemini).
- Chrono job (start/finish), repositionnement carte (set-location), vue satellite,
  Street View clic-droit, année devant les dates dues groupées.
- Sync techniciens : rapport de réconciliation 3 systèmes (staff legacy / Dispatch
  Technician / groupe Authentik), application MANUELLE, zéro écriture Authentik (+11 fiches).
- vision.js : extractEquipment() réutilisable (marque/modèle/série/MAC/codes-barres).
- Pont legacy (ops_reassign.php) : désassignation reflétée, fermeture ticket, retour
  au pool ; notification courriel à l'assignation.

Déployé sur le hub ; ce commit aligne le repo sur l'état en production.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-08 19:47:21 -04:00

253 lines
12 KiB
JavaScript

'use strict'
const cfg = require('./config')
const { log, json, parseBody } = require('./helpers')
const GEMINI_URL = () => `https://generativelanguage.googleapis.com/v1beta/models/${cfg.AI_MODEL}:generateContent?key=${cfg.AI_API_KEY}`
async function geminiVision (base64Image, prompt, schema) {
const resp = await fetch(GEMINI_URL(), {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
contents: [{ parts: [{ text: prompt }, { inline_data: { mime_type: 'image/jpeg', data: base64Image } }] }],
generationConfig: { temperature: 0.1, maxOutputTokens: 1024, responseMimeType: 'application/json', responseSchema: schema },
}),
})
if (!resp.ok) { const t = await resp.text(); throw new Error(`Gemini API ${resp.status}: ${t.slice(0, 200)}`) }
const data = await resp.json()
const text = (data.candidates?.[0]?.content?.parts?.[0]?.text || '').trim()
log(`Vision response: ${text.slice(0, 300)}`)
let parsed
try { parsed = JSON.parse(text) } catch { const m = text.match(/\{[\s\S]*\}/); if (m) try { parsed = JSON.parse(m[0]) } catch {} }
return parsed
}
function extractBase64 (req, body, label) {
if (!cfg.AI_API_KEY) return { error: 'AI_API_KEY not configured', status: 500 }
if (!body.image) return { error: 'Missing image field (base64)', status: 400 }
const base64 = body.image.replace(/^data:image\/[^;]+;base64,/, '')
log(`Vision ${label}: received image ${Math.round(base64.length * 3 / 4 / 1024)}KB`)
return { base64 }
}
const BARCODE_PROMPT = `Read ALL identifiers on this equipment label photo (may be blurry/tilted).
Extract: barcode text, serial numbers (S/N, SN), MAC addresses (12 hex chars), model numbers (M/N, Model, P/N), IMEI, GPON SN.
Examples: 1608K44D9E79FAFF5, TPLG-A1B2C3D4, 04:18:D6:A1:B2:C3, HWTC87654321.
Try your BEST on every character. Return max 3 most important (serial/MAC first).`
const BARCODE_SCHEMA = {
type: 'object',
properties: { barcodes: { type: 'array', items: { type: 'string' }, maxItems: 3 } },
required: ['barcodes'],
}
async function handleBarcodes (req, res) {
const body = await parseBody(req)
const check = extractBase64(req, body, 'barcode')
if (check.error) return json(res, check.status, { error: check.error })
try {
const result = await extractBarcodes(check.base64)
return json(res, 200, result)
} catch (e) {
log('Vision barcode error:', e.message)
return json(res, 500, { error: 'Vision extraction failed: ' + e.message })
}
}
async function extractBarcodes (base64Image) {
const parsed = await geminiVision(base64Image, BARCODE_PROMPT, BARCODE_SCHEMA)
if (!parsed) return { barcodes: [] }
const arr = Array.isArray(parsed) ? parsed : Array.isArray(parsed.barcodes) ? parsed.barcodes : []
const barcodes = arr.filter(v => typeof v === 'string' && v.trim().length > 3).map(v => v.trim().replace(/\s+/g, '')).slice(0, 3)
log(`Vision: extracted ${barcodes.length} barcode(s): ${barcodes.join(', ')}`)
return { barcodes }
}
const EQUIP_PROMPT = `Read this ISP equipment label (ONT/ONU/router/modem). Return structured JSON.
Extract: brand/manufacturer, model (M/N, P/N), serial (S/N, SN, under barcode), MAC address (12 hex, no separators), GPON SN, HW version, barcodes.
Try your BEST on blurry/angled text. Set missing fields to null.`
const EQUIP_SCHEMA = {
type: 'object',
properties: {
brand: { type: 'string', nullable: true }, model: { type: 'string', nullable: true },
serial_number: { type: 'string', nullable: true }, mac_address: { type: 'string', nullable: true },
gpon_sn: { type: 'string', nullable: true }, hw_version: { type: 'string', nullable: true },
equipment_type: { type: 'string', nullable: true },
barcodes: { type: 'array', items: { type: 'string' }, maxItems: 5 },
},
required: ['serial_number'],
}
// Extraction équipement réutilisable (étiquette modem/ONU → marque/modèle/série/MAC). base64 SANS préfixe data:.
async function extractEquipment (base64) {
const parsed = await geminiVision(base64, EQUIP_PROMPT, EQUIP_SCHEMA)
if (!parsed) return { serial_number: null, barcodes: [] }
if (parsed.mac_address) parsed.mac_address = parsed.mac_address.replace(/[:\-.\s]/g, '').toUpperCase()
if (parsed.serial_number) parsed.serial_number = parsed.serial_number.replace(/\s+/g, '').trim()
log(`Vision equipment: brand=${parsed.brand} model=${parsed.model} sn=${parsed.serial_number} mac=${parsed.mac_address}`)
return parsed
}
async function handleEquipment (req, res) {
const body = await parseBody(req)
const check = extractBase64(req, body, 'equipment')
if (check.error) return json(res, check.status, { error: check.error })
try { return json(res, 200, await extractEquipment(check.base64)) }
catch (e) { log('Vision equipment error:', e.message); return json(res, 500, { error: 'Vision extraction failed: ' + e.message }) }
}
// ─── Invoice / bill OCR ────────────────────────────────────────────────
// We run this on Gemini (not on Ollama) because the ops VM has no GPU —
// ops must not depend on a local vision model. The schema matches what
// the ops InvoiceScanPage expects so switching away from Ollama is a
// drop-in replacement on the frontend.
const INVOICE_PROMPT = `You are an invoice/bill OCR assistant. Extract structured data from this photo of a vendor invoice or bill.
Return ONLY valid JSON that matches the provided schema. No prose, no markdown.
Rules:
- "date" / "due_date" must be ISO YYYY-MM-DD. If the date is MM/DD/YYYY or DD/MM/YYYY and ambiguous, prefer YYYY-MM-DD with the most likely interpretation for Canadian/Québec invoices.
- "currency" is a 3-letter code (CAD, USD, EUR). Default to CAD if not visible.
- "tax_gst" = GST/TPS/HST (Canadian federal tax); "tax_qst" = QST/TVQ (Québec provincial tax).
- "items" is a line-by-line list; keep description as printed, collapse whitespace.
- Missing fields → null for strings, 0 for numbers, [] for items.`
const INVOICE_SCHEMA = {
type: 'object',
properties: {
vendor: { type: 'string', nullable: true },
vendor_address: { type: 'string', nullable: true },
invoice_number: { type: 'string', nullable: true },
date: { type: 'string', nullable: true },
due_date: { type: 'string', nullable: true },
subtotal: { type: 'number', nullable: true },
tax_gst: { type: 'number', nullable: true },
tax_qst: { type: 'number', nullable: true },
total: { type: 'number', nullable: true },
currency: { type: 'string', nullable: true },
items: {
type: 'array',
items: {
type: 'object',
properties: {
description: { type: 'string', nullable: true },
qty: { type: 'number', nullable: true },
rate: { type: 'number', nullable: true },
amount: { type: 'number', nullable: true },
},
},
},
notes: { type: 'string', nullable: true },
},
required: ['vendor', 'total'],
}
async function handleInvoice (req, res) {
const body = await parseBody(req)
const check = extractBase64(req, body, 'invoice')
if (check.error) return json(res, check.status, { error: check.error })
try {
const parsed = await geminiVision(check.base64, INVOICE_PROMPT, INVOICE_SCHEMA)
if (!parsed) return json(res, 200, { vendor: null, total: null, items: [] })
// Normalize: trim + coerce numbers (model sometimes returns "1,234.56" as string)
for (const k of ['subtotal', 'tax_gst', 'tax_qst', 'total']) {
if (typeof parsed[k] === 'string') parsed[k] = Number(parsed[k].replace(/[^0-9.\-]/g, '')) || 0
}
if (Array.isArray(parsed.items)) {
for (const it of parsed.items) {
for (const k of ['qty', 'rate', 'amount']) {
if (typeof it[k] === 'string') it[k] = Number(it[k].replace(/[^0-9.\-]/g, '')) || 0
}
}
}
log(`Vision invoice: vendor=${parsed.vendor} total=${parsed.total} items=${(parsed.items || []).length}`)
return json(res, 200, parsed)
} catch (e) {
log('Vision invoice error:', e.message)
return json(res, 500, { error: 'Vision extraction failed: ' + e.message })
}
}
// ─── Field-targeted extraction (for tech mobile form auto-fill) ─────────
// Instead of "read everything on the label", this pulls ONE specific value.
// Used when a tech has selected e.g. "Wi-Fi password" and wants Gemini to
// find only that field on the sticker. Returns {value, confidence}.
const FIELD_CONFIG = {
serial_number: {
desc: 'the device SERIAL NUMBER (labeled S/N, SN, Serial, N/S). Usually 8-20 alphanumeric chars, frequently printed under a Code128 barcode.',
clean: v => v.replace(/\s+/g, '').toUpperCase(),
},
mac_address: {
desc: 'the MAC ADDRESS (12 hexadecimal chars, may be separated by colons, dashes or nothing). Labeled MAC, WAN MAC, LAN MAC, Ethernet, Wi-Fi MAC.',
clean: v => v.replace(/[^0-9A-F]/gi, '').toUpperCase(),
},
gpon_sn: {
desc: 'the GPON SN — a 4-letter manufacturer code followed by 8 hex characters (e.g. HWTC12345678, ZTEG87654321, CIGG1A2B3C4D). Labeled GPON SN, GPON-SN, ONU SN.',
clean: v => v.replace(/\s+/g, '').toUpperCase(),
},
model: {
desc: 'the MODEL number/name (labeled M/N, Model, P/N, Product, Type). Usually short, e.g. "HG8245H", "TL-WR841N", "HS8145V".',
clean: v => v.trim(),
},
wifi_ssid: {
desc: 'the Wi-Fi NETWORK NAME (SSID). Labeled SSID, Wi-Fi name, WLAN SSID, Nom Wi-Fi, Nom du réseau.',
clean: v => v.trim(),
},
wifi_password: {
desc: 'the Wi-Fi PASSWORD / KEY. Labeled WPA, WPA2, WPA Key, Wi-Fi Password, Wireless Password, Clé Wi-Fi, Mot de passe Wi-Fi, Password, Passphrase. Usually 8-20 chars, mixed case with numbers and sometimes symbols.',
clean: v => v.trim(),
},
imei: {
desc: 'the IMEI (15 digits, exactly). Labeled IMEI.',
clean: v => v.replace(/\D/g, ''),
},
generic: {
desc: 'the requested value (see context hint below)',
clean: v => v.trim(),
},
}
const FIELD_SCHEMA = {
type: 'object',
properties: {
value: { type: 'string', nullable: true },
confidence: { type: 'number' },
},
required: ['value', 'confidence'],
}
async function extractField (base64Image, field, context = {}) {
const config = FIELD_CONFIG[field] || FIELD_CONFIG.generic
const eq = context.equipment_type ? `Equipment type hint: ${context.equipment_type}.` : ''
const brand = context.brand ? `Brand hint: ${context.brand}.` : ''
const model = context.model ? `Model hint: ${context.model}.` : ''
const custom = (field === 'generic' && context.hint) ? `Look for: ${context.hint}.` : ''
const prompt = `You are reading an ISP equipment label (ONT, router, modem). Extract ${config.desc}
${eq} ${brand} ${model} ${custom}
Return ONLY JSON matching the schema: {"value": "<the raw extracted text without its label prefix>", "confidence": <0.0-1.0>}.
If you cannot find it with confidence above 0.5, return {"value": null, "confidence": 0.0}.
Do NOT invent data. Prefer returning null over guessing.`
const parsed = await geminiVision(base64Image, prompt, FIELD_SCHEMA)
if (!parsed || !parsed.value) return { value: null, confidence: 0 }
const cleaned = config.clean(parsed.value)
if (!cleaned) return { value: null, confidence: 0 }
return { value: cleaned, confidence: Math.max(0, Math.min(1, Number(parsed.confidence) || 0.5)) }
}
async function handleFieldScan (req, res) {
const body = await parseBody(req)
const check = extractBase64(req, body, 'field-scan')
if (check.error) return json(res, check.status, { error: check.error })
try {
const out = await extractField(check.base64, body.field || 'generic', {
hint: body.hint, equipment_type: body.equipment_type, brand: body.brand, model: body.model,
})
return json(res, 200, { ok: true, ...out })
} catch (e) {
log('Vision field-scan error:', e.message)
return json(res, 500, { error: 'Vision field extraction failed: ' + e.message })
}
}
module.exports = { handleBarcodes, extractBarcodes, handleEquipment, extractEquipment, handleInvoice, extractField, handleFieldScan }