Files
accounted/extensions/general/invoice-inbox/lib/extract-invoice-fields.ts
T
MattssonandClaude Fable 5 516e8b62ff feat(inbox): match non-invoice documents via prominent amounts (#2048)
* feat(inbox): match non-invoice documents via prominent amounts

Bankintyg, bank agreements and other documentKind "other" PDFs carry no
invoice-style total, so extraction correctly left totals.total null and the
document became structurally unmatchable: findUnderlagCandidates hard-drops
items without a comparable amount and the picker lost the 40% amount signal.

- extraction: new prominentAmounts[] field (amount + document's own label),
  populated only when totals.total is null; account/org/phone/reference
  numbers and zero amounts excluded. totals.total semantics untouched.
- matching: bestProminentAmountVariance() tries each printed amount and
  feeds calculateMatchConfidence at reduced weight (0.3 vs 0.4) in both the
  agent candidate scorer and TransactionMatchPicker.
- UI: inbox rail shows the detected amounts read-only for such documents,
  list falls back to a single distinct prominent amount, and extraction no
  longer reads as "found nothing".

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Hqm9QgdyNAFaWiz6Ww7pgb

* fix(inbox): discount prominent-amount fallback instead of reweighting it

Skeptic pass refutations on the first commit: normalized weighting made a
reduced amount weight self-defeating. Date + exact fallback amount with no
merchant scored (0.25+0.3)/0.55 = 1.0 ("100% sakerhet" on a wrong same-day
transaction), and a DISAGREEING fallback amount scored above a disagreeing
invoice total (0.67 vs 0.60) because shrinking the weight also shrank the
penalty.

- score fallbacks at full amount weight, then multiply by a flat
  FALLBACK_CONFIDENCE_FACTOR (0.85): agreement caps below certainty,
  disagreement stays at least as damning as for a real total.
- agent candidate surface additionally requires the document date within
  DATE_TOLERANCE_DAYS, so an avtal listing 349 kr no longer matches every
  future 349 kr charge from the same counterparty.
- bestProminentAmountVariance returns which amount matched + its document
  label, and the match reason names it ("Exakt belopp i dokumentet: 2 500
  SEK (Engangspris)"): no more bare "Exakt belopp" reaching the agent while
  total_amount is null.
- prompt: prominentAmounts restricted to non-invoice documentKinds, and
  never a parking spot for an unreadable invoice total.
- fix the stale "deliberately the same list" comment on
  EXTRACTED_FIELD_ACCESSORS.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Hqm9QgdyNAFaWiz6Ww7pgb

* fix(receipt-hunt): never propose on the prominent-amounts fallback

Second skeptic pass: the nightly hunt is a third consumer of
scoreUnderlagCandidates and inherited the fallback unaware. A bankintyg
whose printed "Insatt belopp" equals a same-day outflow scores 0.85, which
clears CERTAIN_CONFIDENCE (0.8) and skips LLM adjudication, on a pairing
wrong by construction (the hunt scans outflows only; "Insatt belopp"
labels an inflow), with document_amount null in the approval preview.

UnderlagCandidate now carries amountSource ('total' | 'prominent') and
selectProposals drops fallback-scored candidates. Non-invoice documents
stay reachable through the manual picker and the agent candidate surface,
both of which have a human reading the amounts.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Hqm9QgdyNAFaWiz6Ww7pgb

* fix(inbox): round fallback confidence via roundOre, not the naive pattern

The two confidence discounts (and their test) tripped the naive-ore-round
antipattern ratchet (625 vs baseline 622); use the sanctioned helper.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Hqm9QgdyNAFaWiz6Ww7pgb

---------

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
2026-08-30 23:52:29 +02:00

648 lines
28 KiB
TypeScript

// AI-driven invoice/receipt field extraction.
//
// Sends the uploaded document to the configured AI backend through the
// job-shaped service in lib/ai (Claude on Bedrock or the direct API on
// hosted; any OpenAI-compatible endpoint, e.g. a Swedish inference provider,
// on a sovereign self-host) and asks for a structured InvoiceExtractionResult
// JSON. Vision models read PDFs, images and scans, which the previous regex
// extractor couldn't: that's why English receipts (Anthropic, AWS, Stripe, …)
// and image-only PDFs came back empty.
//
// The AI output is validated against a Zod schema; anything that doesn't
// parse falls back to an empty result so the inbox row still lands and
// the user can fill the fields in manually.
import { createHash } from 'node:crypto'
import { z } from 'zod'
import type { InvoiceExtractionResult } from '@/types'
import { getAiService, readAiConfig, extractJsonObject } from '@/lib/ai'
import type { AiDocumentInput, AiImageMediaType, ExtractionSkipReason } from '@/lib/ai'
import { createLogger } from '@/lib/logger'
// Re-exported for callers and tests that import it from here.
export { extractJsonObject }
const log = createLogger('invoice-inbox-extract')
// Output cap: AI_EXTRACTION_MAX_TOKENS (legacy BEDROCK_MAX_TOKENS) or 8192,
// enough headroom for invoices with 20+ line items. The model id per tier is
// resolved by lib/ai/config.ts (AI_EXTRACTION_MODEL, legacy BEDROCK_MODEL_ID,
// AI_MODEL, then the Claude default on the Anthropic family).
// Media types the extraction accepts. HEIC/HEIF are not on the list, so we
// skip AI for those: the inbox row still lands and the user can edit fields
// manually or replace the file. text/html (mail-body invoices from the
// inbound pipeline) is not sent as a document block: it is converted to plain
// text via htmlToText() first, which also makes it work on text-only models.
const SUPPORTED_MEDIA_TYPES = new Set([
'application/pdf',
'image/jpeg',
'image/png',
'image/webp',
'image/gif',
'text/html',
])
export interface ExtractionInput {
buffer: Buffer
mimeType: string
fileName: string
}
export type ExtractionSkipped = ExtractionSkipReason | 'unsupported_media'
export interface ExtractionOutput {
data: InvoiceExtractionResult
/** The raw JSON string returned by the model, or null on failure/skip. */
rawText: string | null
/** Provider-form id of the model that answered, when a call was made. */
model?: string | null
/** Set when no model call was made at all (and why). */
skipped?: ExtractionSkipped | null
}
// Classification fields are nullable AND .catch(null): a hallucinated enum
// value must degrade to "unknown", never fail the whole document parse. The
// amount/date fields keep strict parsing on purpose: a malformed amount
// SHOULD reject the output rather than store garbage.
const DocumentKind = z
.enum(['receipt', 'supplier_invoice', 'government_letter', 'other'])
.nullable()
.catch(null)
const PaymentMethod = z
.enum(['card', 'swish', 'cash', 'invoice', 'other'])
.nullable()
.catch(null)
const MerchantCategory = z
.enum(['restaurant', 'cafe', 'taxi', 'parking', 'fuel', 'grocery', 'hotel', 'other'])
.nullable()
.catch(null)
const Legibility = z.enum(['good', 'partial', 'unreadable']).nullable().catch(null)
export const ExtractionSchema = z.object({
// All optional: raw model outputs cached before these fields existed must
// still validate (same convention as servicePeriodStart/End below). These
// route UI emphasis and clarifying questions only; they never book anything.
documentKind: DocumentKind.optional(),
merchantCategory: MerchantCategory.optional(),
legibility: Legibility.optional(),
purchaseTime: z
.string()
.regex(/^([01]\d|2[0-3]):[0-5]\d$/)
.nullable()
.catch(null)
.optional(),
payment: z
.object({
method: PaymentMethod,
// Length + digits-only, deliberately not the shared four-digit
// invariant from @/lib/invariants: this is the tail of a masked card
// number, not a BAS account and not a fiscal year.
cardLast4: z.string().length(4).regex(/^\d+$/).nullable().catch(null),
})
.nullable()
.catch(null)
.optional(),
supplier: z.object({
name: z.string().nullable(),
orgNumber: z.string().nullable(),
vatNumber: z.string().nullable(),
address: z.string().nullable(),
bankgiro: z.string().nullable(),
plusgiro: z.string().nullable(),
}),
invoice: z.object({
invoiceNumber: z.string().nullable(),
invoiceDate: z.string().nullable(),
dueDate: z.string().nullable(),
paymentReference: z.string().nullable(),
currency: z.string(),
// Service/coverage window the invoice charges for (insurance period,
// license term, "avtalsperiod"). Drives the periodisering prefill in the
// supplier-invoice form. Optional so cached raw outputs from before this
// field still validate.
servicePeriodStart: z.string().nullable().optional(),
servicePeriodEnd: z.string().nullable().optional(),
}),
lineItems: z.array(
z.object({
description: z.string(),
quantity: z.number(),
unitPrice: z.number().nullable(),
lineTotal: z.number(),
// Sane range for any real-world VAT rate. We allow non-Swedish rates
// (UK 20, DE 19, NO 25, ...) since Accounted stores foreign invoices
// for reference; the strict Swedish allowlist applies later when the
// user converts to a supplier invoice.
vatRate: z.number().min(0).max(100).nullable(),
// accountSuggestion is forcibly null at parse time: we never
// delegate BAS account assignment to an unvalidated AI output.
// .transform coerces a hallucinated string to null without
// failing the whole document parse, and eliminates the
// post-validation null-forcing pattern that left a brief window
// where a non-null value could appear in the parsed object.
accountSuggestion: z.union([z.string(), z.null()]).transform(() => null as null),
})
),
totals: z.object({
subtotal: z.number().nullable(),
vatAmount: z.number().nullable(),
total: z.number().nullable(),
// Öresavrundning line on Swedish receipts (can be negative). Optional so
// cached raw outputs from before the field still validate.
roundingAmount: z.number().nullable().catch(null).optional(),
}),
vatBreakdown: z.array(
z.object({
rate: z.number().min(0).max(100),
base: z.number(),
amount: z.number(),
})
),
// Amounts visible on non-invoice documents (bankintyg, avtal, contracts)
// that carry no invoice-style total. Matching hint only; never booked.
// .catch([]) so a hallucinated shape degrades to "no amounts" instead of
// failing the whole document parse; optional so cached raw outputs from
// before the field existed still validate.
prominentAmounts: z
.array(
z.object({
amount: z.number(),
label: z.string().nullable(),
})
)
.catch([])
.optional(),
})
// Agent-supplied extraction: accountSuggestion is preserved instead of forced
// to null. Agents (unlike AI extractors) can reliably assign a BAS expense
// account; the regex enforces the class-4-7 range required for cost accounts.
export const AgentExtractionSchema = ExtractionSchema.omit({ lineItems: true }).extend({
lineItems: z.array(
z.object({
description: z.string(),
quantity: z.number(),
unitPrice: z.number().nullable(),
lineTotal: z.number(),
vatRate: z.number().min(0).max(100).nullable(),
accountSuggestion: z.string().regex(/^[4-7]\d{3}$/).nullable(),
})
),
})
const SYSTEM_PROMPT = `You extract invoice and receipt fields from a single document for a Swedish accounting system.
Return ONLY a single JSON object that matches this schema exactly. No prose, no markdown fences, no commentary.
{
"documentKind": "receipt" | "supplier_invoice" | "government_letter" | "other" | null,
"merchantCategory": "restaurant" | "cafe" | "taxi" | "parking" | "fuel" | "grocery" | "hotel" | "other" | null,
"legibility": "good" | "partial" | "unreadable",
"purchaseTime": string | null, // "HH:MM" 24h, receipts only
"payment": { "method": "card" | "swish" | "cash" | "invoice" | "other" | null, "cardLast4": string | null } | null,
"supplier": {
"name": string | null,
"orgNumber": string | null, // 10 digits, no hyphen, only when issued by a Swedish entity
"vatNumber": string | null, // ISO format, e.g. "SE556012579001" or "DE123456789"
"address": string | null, // multi-line allowed
"bankgiro": string | null, // Swedish bankgiro, with hyphen, e.g. "991-2346"
"plusgiro": string | null // Swedish plusgiro, with hyphen, e.g. "12345-6"
},
"invoice": {
"invoiceNumber": string | null, // include any suffix, e.g. "06655767-0007"
"invoiceDate": string | null, // ISO date YYYY-MM-DD
"dueDate": string | null, // ISO date YYYY-MM-DD
"paymentReference": string | null, // OCR / payment reference
"currency": string, // ISO 4217 (SEK, USD, EUR, ...). Default "SEK" only if truly indeterminate.
"servicePeriodStart": string | null, // ISO date: start of the service/coverage window the invoice charges for
"servicePeriodEnd": string | null // ISO date: end of that window
},
"lineItems": [
{
"description": string,
"quantity": number,
"unitPrice": number | null,
"lineTotal": number,
"vatRate": number | null, // percent integer: 25, 12, 6, or 0. Same convention as vatBreakdown.rate.
"accountSuggestion": null // always null: leave Swedish BAS suggestion to the user
}
],
"totals": {
"subtotal": number | null, // amount excluding VAT
"vatAmount": number | null, // total VAT
"total": number | null, // amount including VAT: what the buyer actually pays
"roundingAmount": number | null // öresavrundning line, may be negative, e.g. -0.37
},
"vatBreakdown": [
{ "rate": number, "base": number, "amount": number } // rate as percent integer, e.g. 25 for 25%
],
"prominentAmounts": [
{ "amount": number, "label": string | null } // non-invoice documents only, see rules
]
}
VAT rate convention: BOTH lineItems[].vatRate AND vatBreakdown[].rate use the same percent-integer format (25, 12, 6, 0). Never use the decimal form (0.25, 0.12).
Rules:
- Output JSON only. The first character must be '{' and the last must be '}'.
- documentKind: "receipt" = point-of-sale proof of a COMPLETED payment (kassakvitto, kortkvitto, taxi/parking slip, webshop order confirmation marked paid). "supplier_invoice" = a request for payment (has due date, OCR/payment reference, bankgiro, "Att betala senast"). "government_letter" = correspondence from a myndighet (Skatteverket, Bolagsverket, Försäkringskassan...). "other" = contracts, statements, reports. null only when truly indeterminate.
- merchantCategory: judge from the merchant name and line items (a receipt from "Prinsen" listing food and wine is "restaurant" even without the word). Use "other" when unsure. null for non-receipts.
- legibility: "good" = all key amounts and the merchant are readable. "partial" = some key fields are cut off, blurry, or unreadable. "unreadable" = the document is mostly illegible (too blurry/dark/small). Judge the IMAGE quality, not whether fields exist on the document.
- payment: only for documents that show how payment was made. "card" for kort/VISA/Mastercard; cardLast4 only when a masked card number like ****1234 is printed. "invoice" means the document says it will be billed separately.
- purchaseTime: the HH:MM time printed on a receipt. null when absent.
- Öresavrundning: Swedish receipts often show an "Avrundning"/"Öresavrundning" line. "total" is ALWAYS the amount actually paid AFTER rounding; put the rounding line in totals.roundingAmount (negative when rounded down). When present: subtotal + vatAmount + roundingAmount = total.
- Currency: detect from the document (symbol $/€/kr or explicit code). Use the ISO 4217 code. Do NOT default to SEK if the document clearly shows another currency.
- "total" is the amount the buyer must pay (look for "Att betala", "Total", "Amount paid", "Amount due", "Balance"). Prefer this over Subtotal.
- Dates: convert any format to YYYY-MM-DD. If the document only shows month/year, leave null.
- servicePeriodStart/servicePeriodEnd: only when the document explicitly states the period the charge covers ("Avtalsperiod", "Period", "Försäkringstid", "Subscription period", coverage dates). Never infer from invoice/due dates. Month-only boundaries map to the first resp. last day of the month.
- Bankgiro/Plusgiro: only set when the document is for a Swedish supplier on a Swedish bank rail. Do not invent.
- Org.nr: only set when it is an actual Swedish organisation number (10 digits, Luhn-valid). For US/EU companies leave null even if they list an EIN/VAT number.
- VAT number: include the country prefix.
- Numbers: parse with the document's locale (Swedish "1 234,56" = 1234.56; English "$1,234.56" = 1234.56). Output as plain JSON numbers.
- If a field is missing or unreadable, set it to null. Never invent values.
- lineItems: include every line. Empty array is fine if the document has no itemised lines.
- vatBreakdown: include one entry per distinct VAT rate. Empty array is fine.
- prominentAmounts: ONLY for documents that are NOT invoices or receipts (documentKind "other" or "government_letter") AND where totals.total is null, when the document still displays clear monetary amounts (a price, fee, deposit or paid-in sum: "Engångspris", "Anslutningspris", "Insatt belopp", "Månadspris", "Pris", "Belopp"). Typical sources: bankintyg, bank/account agreements, contracts, statements. One entry per distinct amount, label = the document's own label for it. NEVER include account numbers, org numbers, phone numbers, OCR/reference numbers, dates, percentages, or zero amounts. ALWAYS an empty array for invoices and receipts, including ones whose total is unreadable: never move an invoice total here.`
export function emptyResult(): InvoiceExtractionResult {
return {
documentKind: null,
merchantCategory: null,
legibility: null,
purchaseTime: null,
payment: null,
supplier: {
name: null,
orgNumber: null,
vatNumber: null,
address: null,
bankgiro: null,
plusgiro: null,
},
invoice: {
invoiceNumber: null,
invoiceDate: null,
dueDate: null,
paymentReference: null,
currency: 'SEK',
servicePeriodStart: null,
servicePeriodEnd: null,
},
lineItems: [],
totals: { subtotal: null, vatAmount: null, total: null, roundingAmount: null },
vatBreakdown: [],
prominentAmounts: [],
confidence: 0,
}
}
// Anthropic rejects images above 5 MB (decoded bytes), and 12 MP phone photos
// routinely exceed that: before this step they errored out to an empty
// extraction. Downscaling to ≤2000px JPEG also cuts input tokens on every
// large image. HEIC/HEIF (iPhone default) is transcoded to JPEG when the
// local sharp/libvips build can decode it; prebuilt binaries usually cannot
// (patent licensing), in which case the caller falls through to the
// unsupported-type path exactly as before.
const IMAGE_DOWNSCALE_THRESHOLD_BYTES = 4 * 1024 * 1024
const IMAGE_MAX_DIMENSION = 2000
async function normalizeImageForExtraction(
input: ExtractionInput
): Promise<ExtractionInput> {
const isHeic = input.mimeType === 'image/heic' || input.mimeType === 'image/heif'
const isLargeSupportedImage =
input.mimeType.startsWith('image/') &&
SUPPORTED_MEDIA_TYPES.has(input.mimeType) &&
input.buffer.byteLength > IMAGE_DOWNSCALE_THRESHOLD_BYTES
if (!isHeic && !isLargeSupportedImage) return input
try {
// Lazy import: sharp is a native module and only a fraction of
// extractions need it; loading it at module scope would tax every
// cold start of the extension route bundle.
const sharp = (await import('sharp')).default
const converted = await sharp(input.buffer)
// Apply the EXIF orientation before it is lost in re-encoding:
// phone photos are routinely stored rotated.
.rotate()
.resize({
width: IMAGE_MAX_DIMENSION,
height: IMAGE_MAX_DIMENSION,
fit: 'inside',
withoutEnlargement: true,
})
.jpeg({ quality: 80 })
.toBuffer()
return { buffer: converted, mimeType: 'image/jpeg', fileName: input.fileName }
} catch (err) {
// HEIC without libheif lands here → caller hits the unsupported-type
// guard, same net behavior as before this step existed. For oversized
// JPEG/PNG the original buffer is still worth attempting.
log.warn('image normalization failed', {
file_name_hash: createHash('sha256').update(input.fileName).digest('hex').slice(0, 12),
mime_type: input.mimeType,
byte_length: input.buffer.byteLength,
error: err instanceof Error ? err.message : String(err),
})
return input
}
}
// Cap the text handed to the model. HTML mails can carry hundreds of KB of
// framework markup; the invoice fields sit in the first fraction of the
// visible text, and MAX_TOKENS bounds the output side anyway.
const MAX_EXTRACTION_TEXT_LENGTH = 50_000
/**
* Best-effort HTML-to-text for mail-body invoices. Not a sanitiser (the
* output is only ever sent to the model as plain text, never rendered):
* drops script/style/head blocks and comments, keeps block boundaries as
* newlines so amounts and labels stay line-separated, decodes the entities
* that occur in practice, and collapses whitespace.
*/
export function htmlToText(html: string): string {
const withoutBlocks = html
.replace(/<(script|style|head|title)\b[^>]*>[\s\S]*?<\/\1\s*>/gi, ' ')
.replace(/<!--[\s\S]*?-->/g, ' ')
const withBreaks = withoutBlocks
.replace(/<\/(p|div|tr|li|h[1-6]|table|thead|tbody|section|article|blockquote|pre)\s*>/gi, '\n')
.replace(/<(br|hr)\b[^>]*\/?>/gi, '\n')
const stripped = withBreaks.replace(/<[^>]+>/g, ' ')
const decoded = stripped
.replace(/&nbsp;/gi, ' ')
.replace(/&lt;/gi, '<')
.replace(/&gt;/gi, '>')
.replace(/&quot;/gi, '"')
.replace(/&apos;/gi, "'")
.replace(/&#(\d+);/g, (_, n: string) => {
const code = Number(n)
return code > 31 && code <= 0x10ffff ? String.fromCodePoint(code) : ' '
})
.replace(/&#x([0-9a-f]+);/gi, (_, n: string) => {
const code = parseInt(n, 16)
return code > 31 && code <= 0x10ffff ? String.fromCodePoint(code) : ' '
})
// &amp; strictly last: decoding it earlier would double-decode
// "&amp;lt;" into "<" instead of the literal "&lt;".
.replace(/&amp;/gi, '&')
return decoded
.replace(/[ \t]+/g, ' ')
.replace(/\s*\n\s*/g, '\n')
.replace(/\n{3,}/g, '\n\n')
.trim()
.slice(0, MAX_EXTRACTION_TEXT_LENGTH)
}
const EXTRACTION_INSTRUCTION = 'Extract the fields per the schema. JSON only.'
/** Map an upload to the service's document input. HTML becomes plain text. */
function toDocumentInput(input: ExtractionInput): AiDocumentInput {
if (input.mimeType === 'text/html') {
const text = htmlToText(input.buffer.toString('utf8'))
return {
kind: 'text',
text: `The document is an HTML email invoice, converted to plain text:\n\n${text}`,
}
}
if (input.mimeType === 'application/pdf') {
return { kind: 'pdf', data: input.buffer, fileName: input.fileName }
}
return { kind: 'image', data: input.buffer, mediaType: input.mimeType as AiImageMediaType }
}
// Hand-maintained JSON-schema mirror of ExtractionSchema, used ONLY when the
// operator opts into strict JSON mode on an OpenAI-compatible endpoint
// (AI_STRICT_JSON=true). Deliberately not auto-converted from the Zod schema:
// .catch()/.transform() have no JSON-schema equivalent and the conversion
// would drift silently. Permissive on purpose (types + nullability only):
// Zod stays the validator, this just keeps the model inside the shape.
const nullable = (type: string) => ({ type: [type, 'null'] })
const EXTRACTION_JSON_SCHEMA: Record<string, unknown> = {
type: 'object',
additionalProperties: false,
properties: {
documentKind: nullable('string'),
merchantCategory: nullable('string'),
legibility: nullable('string'),
purchaseTime: nullable('string'),
payment: {
type: ['object', 'null'],
additionalProperties: false,
properties: { method: nullable('string'), cardLast4: nullable('string') },
required: ['method', 'cardLast4'],
},
supplier: {
type: 'object',
additionalProperties: false,
properties: {
name: nullable('string'),
orgNumber: nullable('string'),
vatNumber: nullable('string'),
address: nullable('string'),
bankgiro: nullable('string'),
plusgiro: nullable('string'),
},
required: ['name', 'orgNumber', 'vatNumber', 'address', 'bankgiro', 'plusgiro'],
},
invoice: {
type: 'object',
additionalProperties: false,
properties: {
invoiceNumber: nullable('string'),
invoiceDate: nullable('string'),
dueDate: nullable('string'),
paymentReference: nullable('string'),
currency: { type: 'string' },
servicePeriodStart: nullable('string'),
servicePeriodEnd: nullable('string'),
},
required: [
'invoiceNumber',
'invoiceDate',
'dueDate',
'paymentReference',
'currency',
'servicePeriodStart',
'servicePeriodEnd',
],
},
lineItems: {
type: 'array',
items: {
type: 'object',
additionalProperties: false,
properties: {
description: { type: 'string' },
quantity: { type: 'number' },
unitPrice: nullable('number'),
lineTotal: { type: 'number' },
vatRate: nullable('number'),
accountSuggestion: { type: 'null' },
},
required: ['description', 'quantity', 'unitPrice', 'lineTotal', 'vatRate', 'accountSuggestion'],
},
},
totals: {
type: 'object',
additionalProperties: false,
properties: {
subtotal: nullable('number'),
vatAmount: nullable('number'),
total: nullable('number'),
roundingAmount: nullable('number'),
},
required: ['subtotal', 'vatAmount', 'total', 'roundingAmount'],
},
vatBreakdown: {
type: 'array',
items: {
type: 'object',
additionalProperties: false,
properties: { rate: { type: 'number' }, base: { type: 'number' }, amount: { type: 'number' } },
required: ['rate', 'base', 'amount'],
},
},
prominentAmounts: {
type: 'array',
items: {
type: 'object',
additionalProperties: false,
properties: { amount: { type: 'number' }, label: nullable('string') },
required: ['amount', 'label'],
},
},
},
required: [
'documentKind',
'merchantCategory',
'legibility',
'purchaseTime',
'payment',
'supplier',
'invoice',
'lineItems',
'totals',
'vatBreakdown',
'prominentAmounts',
],
}
/**
* Extract invoice fields by sending the document to the configured AI
* backend. Never throws on extraction failure: always returns an
* InvoiceExtractionResult. Empty fields are null. `skipped` is set when no
* model call was made (unsupported file type, AI not configured, no vision
* on this backend, PDF rasterizer missing), so callers can tell "nothing to
* read" from "read and found nothing".
*/
export async function extractInvoiceFields(
rawInput: ExtractionInput
): Promise<ExtractionOutput> {
// Transcodes HEIC when possible and downscales oversized images; a no-op
// for PDFs and normal-sized supported images.
const input = await normalizeImageForExtraction(rawInput)
if (!SUPPORTED_MEDIA_TYPES.has(input.mimeType)) {
return { data: emptyResult(), rawText: null, skipped: 'unsupported_media' }
}
const fileNameHash = createHash('sha256').update(input.fileName).digest('hex').slice(0, 12)
const service = getAiService()
let rawText: string | null = null
let model: string | null = null
try {
const baseMaxTokens = readAiConfig().extractionMaxTokens
const request = {
document: toDocumentInput(input),
system: SYSTEM_PROMPT,
instruction: EXTRACTION_INSTRUCTION,
jsonSchema: EXTRACTION_JSON_SCHEMA,
}
let result = await service.extractFromDocument({ ...request, maxTokens: baseMaxTokens })
if (!result.ok) {
// Not a failure: the deployment cannot read this document at all.
// `ai_unconfigured` is the self-host "no key yet" case the 30 s
// upload hang used to hide; the others are honest capability gaps.
log.warn('AI extraction skipped', { file_name_hash: fileNameHash, reason: result.skipped })
return { data: emptyResult(), rawText: null, skipped: result.skipped }
}
if (result.truncated) {
// The output hit maxTokens mid-JSON (line-item-heavy documents). Left
// alone this parsed to nothing and looked like an unreadable document;
// one retry at double the cap recovers it. A second truncation falls
// through to the normal parse path, which fails visibly in the log
// below instead of silently.
log.warn('ai_extraction_truncated', {
file_name_hash: fileNameHash,
max_tokens: baseMaxTokens,
retrying: true,
})
// A retry that THROWS (throttle, network) must not sink the first
// response: its text may still parse despite the truncation flag, and
// the outer catch would otherwise return the empty skeleton with
// rawText null. Swallow locally and continue with the first result.
try {
const retry = await service.extractFromDocument({
...request,
maxTokens: baseMaxTokens * 2,
})
if (retry.ok) {
result = retry
if (retry.truncated) {
log.warn('ai_extraction_truncated', {
file_name_hash: fileNameHash,
max_tokens: baseMaxTokens * 2,
retrying: false,
})
}
}
} catch (retryErr) {
log.warn('ai_extraction_retry_failed', {
file_name_hash: fileNameHash,
error: retryErr instanceof Error ? retryErr.message : String(retryErr),
})
}
}
rawText = result.text
model = result.model
// Observability for the prompt-cache hit ratio. The agent-native plan
// targets cache_read_input_tokens / total_input_tokens ≥ 0.85 in steady
// state; logging here makes that measurable without a separate dashboard.
// Raw fileName can constitute personal data (e.g. "faktura_Sven_Andersson.pdf").
// Log a short hash so the operator can correlate without exposing PII
// to the log destination (GDPR Art. 5(1)(f)).
log.info('ai_extraction_usage', {
file_name_hash: fileNameHash,
mime_type: input.mimeType,
model,
input_tokens: result.usage.inputTokens,
output_tokens: result.usage.outputTokens,
cache_creation_input_tokens: result.usage.cacheCreationInputTokens,
cache_read_input_tokens: result.usage.cacheReadInputTokens,
...(result.pagesRasterized ? { pages_rasterized: result.pagesRasterized } : {}),
})
const parsed = JSON.parse(extractJsonObject(rawText))
const validated = ExtractionSchema.parse(parsed)
return {
// accountSuggestion is null at this point, enforced by the schema's
// .transform, so no post-validation coercion is needed.
data: { ...validated, confidence: 1 },
rawText,
model,
}
} catch (err) {
log.warn('AI extraction failed', {
file_name_hash: fileNameHash,
mimeType: input.mimeType,
error: err instanceof Error ? err.message : String(err),
hasRawText: rawText != null,
})
return { data: emptyResult(), rawText, model }
}
}