feat: unified document inbox, full BAS 2026, and document-transaction matching
- Expand BAS reference from ~180 to ~1,276 accounts (full BAS Kontoplan 2026) with K2 exclusion flags, per-class data files, and computed SRU codes - Evolve invoice inbox into unified document inbox handling invoices, receipts, and government letters with AI-powered classification (Claude Haiku Vision) - Add multi-pass document-to-transaction matching engine with greedy assignment for both supplier invoices (reference/amount/date/name) and receipts (weighted amount/merchant/date scoring) - Add supplier invoice matching in transaction ingest pipeline - Inject booking template suggestions into AI extraction prompts - Surface matched documents in swipe categorization UI with one-tap booking - Auto-activate missing BAS accounts during SIE import against full reference - Add K2 filter toggle in Chart of Accounts manager - Add receipt confirmation route with BFNAR representation fields - Add database migrations for K2 support and document matching columns - Remove obsolete extension migration scripts Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Jakob Wennberg
co-authored by
Claude Opus 4.6
Claude Opus 4.6
parent
6956a757f3
commit
39e407644d
@@ -0,0 +1,238 @@
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import { describe, it, expect, vi, beforeEach } from 'vitest'
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// Mock server-only
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vi.mock('server-only', () => ({}))
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// Mock Anthropic SDK - vi.hoisted ensures the variable is available before vi.mock hoisting
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const { mockCreate } = vi.hoisted(() => {
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const mockCreate = vi.fn()
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return { mockCreate }
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})
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vi.mock('@anthropic-ai/sdk', () => {
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return {
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default: class MockAnthropic {
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messages = { create: mockCreate }
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},
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}
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})
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import { classifyDocument } from '../classifier'
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function makeResponse(json: Record<string, unknown>) {
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return {
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content: [{ type: 'text', text: JSON.stringify(json) }],
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}
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}
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describe('classifyDocument', () => {
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beforeEach(() => {
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vi.clearAllMocks()
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})
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it('classifies a supplier invoice', async () => {
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mockCreate.mockResolvedValueOnce(
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makeResponse({
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type: 'supplier_invoice',
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confidence: 0.95,
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reasoning: 'Contains invoice number, bankgiro, and supplier details',
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isReverseCharge: false,
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})
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)
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const result = await classifyDocument('base64data', 'application/pdf')
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expect(result.type).toBe('supplier_invoice')
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expect(result.confidence).toBe(0.95)
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expect(result.isReverseCharge).toBe(false)
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})
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it('classifies a receipt', async () => {
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mockCreate.mockResolvedValueOnce(
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makeResponse({
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type: 'receipt',
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confidence: 0.92,
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reasoning: 'Store receipt with line items and total',
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})
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)
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const result = await classifyDocument('base64data', 'image/jpeg')
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expect(result.type).toBe('receipt')
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expect(result.confidence).toBe(0.92)
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expect(result.isReverseCharge).toBeUndefined()
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})
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it('classifies a government letter', async () => {
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mockCreate.mockResolvedValueOnce(
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makeResponse({
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type: 'government_letter',
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confidence: 0.88,
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reasoning: 'Letter from Skatteverket',
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})
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)
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const result = await classifyDocument('base64data', 'application/pdf')
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expect(result.type).toBe('government_letter')
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expect(result.confidence).toBe(0.88)
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expect(result.isReverseCharge).toBeUndefined()
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})
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it('classifies unknown documents', async () => {
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mockCreate.mockResolvedValueOnce(
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makeResponse({
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type: 'unknown',
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confidence: 0.5,
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reasoning: 'Cannot determine document type',
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})
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)
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const result = await classifyDocument('base64data', 'image/png')
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expect(result.type).toBe('unknown')
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expect(result.confidence).toBe(0.5)
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})
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it('detects reverse charge on EU invoices', async () => {
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mockCreate.mockResolvedValueOnce(
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makeResponse({
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type: 'supplier_invoice',
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confidence: 0.93,
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reasoning: 'EU invoice with reverse charge',
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isReverseCharge: true,
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})
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)
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const result = await classifyDocument('base64data', 'application/pdf')
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expect(result.type).toBe('supplier_invoice')
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expect(result.isReverseCharge).toBe(true)
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})
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it('retries on API error', async () => {
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mockCreate
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.mockRejectedValueOnce(new Error('API timeout'))
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.mockResolvedValueOnce(
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makeResponse({
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type: 'receipt',
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confidence: 0.9,
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reasoning: 'Receipt',
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})
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)
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const result = await classifyDocument('base64data', 'image/jpeg')
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expect(result.type).toBe('receipt')
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expect(mockCreate).toHaveBeenCalledTimes(2)
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})
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it('throws on JSON parse error without retry', async () => {
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mockCreate.mockResolvedValueOnce({
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content: [{ type: 'text', text: 'not valid json' }],
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})
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await expect(classifyDocument('base64data', 'image/jpeg')).rejects.toThrow(
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'Failed to parse AI response'
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)
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expect(mockCreate).toHaveBeenCalledTimes(1)
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})
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it('throws on unsupported MIME type', async () => {
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await expect(classifyDocument('base64data', 'text/plain')).rejects.toThrow(
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'Unsupported file type: text/plain'
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)
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expect(mockCreate).not.toHaveBeenCalled()
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})
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it('falls back to unknown for invalid type values', async () => {
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mockCreate.mockResolvedValueOnce(
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makeResponse({
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type: 'invalid_type',
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confidence: 0.8,
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reasoning: 'Test',
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})
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)
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const result = await classifyDocument('base64data', 'image/jpeg')
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expect(result.type).toBe('unknown')
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})
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it('handles PDF content blocks correctly', async () => {
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mockCreate.mockResolvedValueOnce(
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makeResponse({
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type: 'supplier_invoice',
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confidence: 0.95,
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reasoning: 'PDF invoice',
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isReverseCharge: false,
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})
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)
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await classifyDocument('base64data', 'application/pdf')
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expect(mockCreate).toHaveBeenCalledWith(
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expect.objectContaining({
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messages: [
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{
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role: 'user',
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content: expect.arrayContaining([
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expect.objectContaining({ type: 'document' }),
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]),
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},
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],
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})
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)
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})
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it('handles image content blocks correctly', async () => {
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mockCreate.mockResolvedValueOnce(
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makeResponse({
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type: 'receipt',
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confidence: 0.9,
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reasoning: 'Image receipt',
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})
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)
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await classifyDocument('base64data', 'image/png')
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expect(mockCreate).toHaveBeenCalledWith(
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expect.objectContaining({
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messages: [
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{
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role: 'user',
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content: expect.arrayContaining([
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expect.objectContaining({ type: 'image' }),
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]),
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},
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],
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})
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)
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})
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it('strips markdown code blocks from response', async () => {
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mockCreate.mockResolvedValueOnce({
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content: [
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{
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type: 'text',
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text: '```json\n{"type":"receipt","confidence":0.9,"reasoning":"Test"}\n```',
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},
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],
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})
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const result = await classifyDocument('base64data', 'image/jpeg')
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expect(result.type).toBe('receipt')
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})
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it('throws after max retries', async () => {
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mockCreate
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.mockRejectedValueOnce(new Error('API error 1'))
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.mockRejectedValueOnce(new Error('API error 2'))
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.mockRejectedValueOnce(new Error('API error 3'))
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await expect(classifyDocument('base64data', 'image/jpeg')).rejects.toThrow(
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'Document classification failed after 3 attempts'
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)
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expect(mockCreate).toHaveBeenCalledTimes(3)
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})
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})
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@@ -0,0 +1,107 @@
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import { describe, it, expect } from 'vitest'
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import {
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levenshteinDistance,
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normalizeMerchantName,
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calculateMerchantSimilarity,
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calculateMatchConfidence,
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} from '../core-receipt-matcher'
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describe('levenshteinDistance', () => {
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it('returns 0 for identical strings', () => {
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expect(levenshteinDistance('abc', 'abc')).toBe(0)
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})
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it('returns length of other string for empty string', () => {
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expect(levenshteinDistance('', 'abc')).toBe(3)
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expect(levenshteinDistance('abc', '')).toBe(3)
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})
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it('calculates correct edit distance', () => {
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expect(levenshteinDistance('kitten', 'sitting')).toBe(3)
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expect(levenshteinDistance('saturday', 'sunday')).toBe(3)
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})
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})
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describe('normalizeMerchantName', () => {
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it('lowercases and trims', () => {
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expect(normalizeMerchantName(' ICA MAXI ')).toBe('ica maxi')
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})
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it('removes Swedish company suffixes', () => {
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expect(normalizeMerchantName('Telia AB')).toBe('telia')
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})
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it('removes special characters but keeps Swedish letters', () => {
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expect(normalizeMerchantName('Café Överkås!')).toBe('café överkås')
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})
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it('collapses whitespace', () => {
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expect(normalizeMerchantName('ica maxi stockholm')).toBe('ica maxi stockholm')
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})
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})
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describe('calculateMerchantSimilarity', () => {
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it('returns 1 for exact match', () => {
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expect(calculateMerchantSimilarity('ICA Maxi', 'ICA Maxi')).toBe(1)
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})
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it('returns 1 for match after normalization', () => {
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expect(calculateMerchantSimilarity('Telia AB', 'telia')).toBe(1)
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})
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it('returns 0.9 when one contains the other', () => {
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expect(calculateMerchantSimilarity('ICA', 'ICA MAXI STOCKHOLM')).toBe(0.9)
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})
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it('returns 0 for empty strings', () => {
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expect(calculateMerchantSimilarity('', 'abc')).toBe(0)
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expect(calculateMerchantSimilarity('abc', '')).toBe(0)
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})
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it('returns score between 0 and 1 for partial matches', () => {
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const score = calculateMerchantSimilarity('ICA Maxi', 'Coop Forum')
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expect(score).toBeGreaterThanOrEqual(0)
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expect(score).toBeLessThanOrEqual(1)
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})
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it('gives high score for word overlap', () => {
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const score = calculateMerchantSimilarity('ICA Maxi Stockholm', 'ICA Maxi Solna')
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expect(score).toBeGreaterThan(0.7)
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})
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})
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describe('calculateMatchConfidence', () => {
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it('gives high confidence for exact date + amount + merchant', () => {
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const { confidence, matchReasons } = calculateMatchConfidence(0, 0, 1.0)
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expect(confidence).toBeGreaterThan(0.9)
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expect(matchReasons).toContain('Exakt datum')
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expect(matchReasons).toContain('Exakt belopp')
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expect(matchReasons).toContain('Handlare matchar')
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})
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it('gives lower confidence when date is off', () => {
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const exact = calculateMatchConfidence(0, 0, 1.0)
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const dateOff = calculateMatchConfidence(2, 0, 1.0)
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expect(dateOff.confidence).toBeLessThan(exact.confidence)
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})
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it('gives lower confidence when amount is off', () => {
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const exact = calculateMatchConfidence(0, 0, 1.0)
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const amountOff = calculateMatchConfidence(0, 0.03, 1.0)
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expect(amountOff.confidence).toBeLessThan(exact.confidence)
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})
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it('gives lower confidence with no merchant similarity when other signals are imperfect', () => {
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// With imperfect date/amount, missing merchant signal lowers overall confidence
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const withMerchant = calculateMatchConfidence(1, 0.02, 0.8)
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const noMerchant = calculateMatchConfidence(1, 0.02, 0)
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expect(noMerchant.confidence).toBeLessThan(withMerchant.confidence)
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})
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it('respects custom tolerances', () => {
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// With wider tolerance, same variance should give higher score
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const narrow = calculateMatchConfidence(2, 0.03, 0.5, 3, 0.05)
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const wide = calculateMatchConfidence(2, 0.03, 0.5, 7, 0.10)
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expect(wide.confidence).toBeGreaterThan(narrow.confidence)
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})
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})
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@@ -0,0 +1,352 @@
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import { describe, it, expect, vi, beforeEach } from 'vitest'
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import { matchDocumentToTransactions } from '../document-matcher'
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import { makeInvoiceInboxItem, makeTransaction } from '@/tests/helpers'
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import type { InvoiceExtractionResult, ReceiptExtractionResult, Transaction } from '@/types'
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describe('matchDocumentToTransactions', () => {
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const mockSupabase = {} as never // Not used when candidateTransactions is provided
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beforeEach(() => {
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vi.clearAllMocks()
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})
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describe('supplier_invoice matching', () => {
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const baseExtraction: InvoiceExtractionResult = {
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supplier: {
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name: 'Telia AB',
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orgNumber: '556103-4249',
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vatNumber: 'SE556103424901',
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address: 'Stockholm',
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bankgiro: '5820-5093',
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plusgiro: null,
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},
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invoice: {
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invoiceNumber: 'INV-2024-001',
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invoiceDate: '2024-06-10',
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dueDate: '2024-06-20',
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paymentReference: '73401284756',
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currency: 'SEK',
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},
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lineItems: [],
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totals: { subtotal: 800, vatAmount: 200, total: 1000 },
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vatBreakdown: [],
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confidence: 0.95,
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}
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it('returns null for government_letter type', async () => {
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const item = makeInvoiceInboxItem({
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document_type: 'government_letter',
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extracted_data: baseExtraction as unknown as Record<string, unknown>,
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})
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const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [])
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expect(result).toBeNull()
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})
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it('returns null when no extracted_data', async () => {
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const item = makeInvoiceInboxItem({ extracted_data: null })
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const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [])
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expect(result).toBeNull()
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})
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it('returns null when no candidate transactions', async () => {
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const item = makeInvoiceInboxItem({
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status: 'ready',
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extracted_data: baseExtraction as unknown as Record<string, unknown>,
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})
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const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [])
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expect(result).toBeNull()
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})
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it('pass 1: matches by payment reference with 0.98 confidence', async () => {
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const item = makeInvoiceInboxItem({
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status: 'ready',
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extracted_data: baseExtraction as unknown as Record<string, unknown>,
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})
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const tx = makeTransaction({
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amount: -1000,
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reference: '73401284756',
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date: '2024-06-20',
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})
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const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
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expect(result).not.toBeNull()
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expect(result!.confidence).toBe(0.98)
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expect(result!.method).toBe('payment_reference')
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expect(result!.transactionId).toBe(tx.id)
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})
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it('pass 1: matches with whitespace/dash-normalized references', async () => {
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const item = makeInvoiceInboxItem({
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status: 'ready',
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extracted_data: baseExtraction as unknown as Record<string, unknown>,
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})
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const tx = makeTransaction({
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amount: -1000,
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reference: '734 012 847 56',
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date: '2024-06-20',
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})
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const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
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expect(result).not.toBeNull()
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expect(result!.confidence).toBe(0.98)
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expect(result!.method).toBe('payment_reference')
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})
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it('pass 2: matches by exact amount + bankgiro with 0.92 confidence', async () => {
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const extractionNoRef = {
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...baseExtraction,
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invoice: { ...baseExtraction.invoice, paymentReference: null },
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}
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const item = makeInvoiceInboxItem({
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status: 'ready',
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extracted_data: extractionNoRef as unknown as Record<string, unknown>,
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})
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const tx = makeTransaction({
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amount: -1000,
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reference: null,
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description: 'BETALNING 58205093',
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date: '2024-06-20',
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})
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const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
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expect(result).not.toBeNull()
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expect(result!.confidence).toBe(0.92)
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expect(result!.method).toBe('payment_reference')
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})
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it('pass 3: matches by exact amount + date proximity with 0.85 confidence', async () => {
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const extractionNoBg = {
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...baseExtraction,
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invoice: { ...baseExtraction.invoice, paymentReference: null },
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supplier: { ...baseExtraction.supplier, bankgiro: null, plusgiro: null },
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}
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const item = makeInvoiceInboxItem({
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status: 'ready',
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extracted_data: extractionNoBg as unknown as Record<string, unknown>,
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})
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const tx = makeTransaction({
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amount: -1000,
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reference: null,
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description: 'PAYMENT',
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date: '2024-06-22',
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merchant_name: null,
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})
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|
||||
const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
|
||||
expect(result).not.toBeNull()
|
||||
expect(result!.confidence).toBe(0.85)
|
||||
expect(result!.method).toBe('amount_date')
|
||||
})
|
||||
|
||||
it('pass 3: matches with lower confidence at 6–14 days', async () => {
|
||||
const extractionNoBg = {
|
||||
...baseExtraction,
|
||||
invoice: { ...baseExtraction.invoice, paymentReference: null },
|
||||
supplier: { ...baseExtraction.supplier, bankgiro: null, plusgiro: null },
|
||||
}
|
||||
const item = makeInvoiceInboxItem({
|
||||
status: 'ready',
|
||||
extracted_data: extractionNoBg as unknown as Record<string, unknown>,
|
||||
})
|
||||
const tx = makeTransaction({
|
||||
amount: -1000,
|
||||
reference: null,
|
||||
description: 'PAYMENT',
|
||||
date: '2024-06-28', // 8 days after due date
|
||||
merchant_name: null,
|
||||
})
|
||||
|
||||
const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
|
||||
expect(result).not.toBeNull()
|
||||
expect(result!.confidence).toBe(0.75)
|
||||
expect(result!.method).toBe('amount_date')
|
||||
})
|
||||
|
||||
it('pass 3: does not match if date is >14 days away', async () => {
|
||||
const extractionNoBg = {
|
||||
...baseExtraction,
|
||||
invoice: { ...baseExtraction.invoice, paymentReference: null },
|
||||
supplier: { ...baseExtraction.supplier, bankgiro: null, plusgiro: null },
|
||||
}
|
||||
const item = makeInvoiceInboxItem({
|
||||
status: 'ready',
|
||||
extracted_data: extractionNoBg as unknown as Record<string, unknown>,
|
||||
})
|
||||
const tx = makeTransaction({
|
||||
amount: -1000,
|
||||
reference: null,
|
||||
description: 'PAYMENT',
|
||||
date: '2024-07-06', // 16 days after due date
|
||||
merchant_name: null,
|
||||
})
|
||||
|
||||
const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
|
||||
expect(result).toBeNull()
|
||||
})
|
||||
|
||||
it('pass 4: matches by fuzzy amount + supplier name with 0.70 confidence', async () => {
|
||||
const extractionMinimal = {
|
||||
...baseExtraction,
|
||||
invoice: {
|
||||
...baseExtraction.invoice,
|
||||
paymentReference: null,
|
||||
dueDate: null,
|
||||
invoiceDate: null,
|
||||
},
|
||||
supplier: {
|
||||
...baseExtraction.supplier,
|
||||
bankgiro: null,
|
||||
plusgiro: null,
|
||||
name: 'Telia Sverige',
|
||||
},
|
||||
}
|
||||
const item = makeInvoiceInboxItem({
|
||||
status: 'ready',
|
||||
extracted_data: extractionMinimal as unknown as Record<string, unknown>,
|
||||
})
|
||||
const tx = makeTransaction({
|
||||
amount: -1000,
|
||||
reference: null,
|
||||
description: 'telia faktura april',
|
||||
date: '2024-06-15',
|
||||
merchant_name: null,
|
||||
})
|
||||
|
||||
const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
|
||||
expect(result).not.toBeNull()
|
||||
expect(result!.confidence).toBe(0.70)
|
||||
expect(result!.method).toBe('amount_merchant')
|
||||
})
|
||||
|
||||
it('prefers higher confidence matches', async () => {
|
||||
const item = makeInvoiceInboxItem({
|
||||
status: 'ready',
|
||||
extracted_data: baseExtraction as unknown as Record<string, unknown>,
|
||||
})
|
||||
|
||||
const txWithRef = makeTransaction({
|
||||
amount: -1000,
|
||||
reference: '73401284756',
|
||||
date: '2024-06-20',
|
||||
})
|
||||
const txWithAmount = makeTransaction({
|
||||
amount: -1000,
|
||||
reference: null,
|
||||
description: 'BETALNING',
|
||||
date: '2024-06-20',
|
||||
})
|
||||
|
||||
const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [txWithAmount, txWithRef])
|
||||
expect(result!.confidence).toBe(0.98)
|
||||
expect(result!.transactionId).toBe(txWithRef.id)
|
||||
})
|
||||
})
|
||||
|
||||
describe('receipt matching', () => {
|
||||
const receiptExtraction: ReceiptExtractionResult = {
|
||||
merchant: {
|
||||
name: 'ICA Maxi',
|
||||
orgNumber: null,
|
||||
vatNumber: null,
|
||||
isForeign: false,
|
||||
},
|
||||
receipt: {
|
||||
date: '2024-06-15',
|
||||
time: '14:30',
|
||||
currency: 'SEK',
|
||||
},
|
||||
lineItems: [],
|
||||
totals: { subtotal: 239.2, vatAmount: 59.8, total: 299 },
|
||||
flags: {
|
||||
isRestaurant: false,
|
||||
isSystembolaget: false,
|
||||
isForeignMerchant: false,
|
||||
},
|
||||
confidence: 0.92,
|
||||
}
|
||||
|
||||
it('matches receipt to transaction with high confidence', async () => {
|
||||
const item = makeInvoiceInboxItem({
|
||||
document_type: 'receipt',
|
||||
status: 'ready',
|
||||
extracted_data: receiptExtraction as unknown as Record<string, unknown>,
|
||||
})
|
||||
const tx = makeTransaction({
|
||||
amount: -299,
|
||||
date: '2024-06-15',
|
||||
merchant_name: 'ICA Maxi',
|
||||
description: 'ICA MAXI STOCKHOLM',
|
||||
})
|
||||
|
||||
const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
|
||||
expect(result).not.toBeNull()
|
||||
expect(result!.method).toBe('receipt_match')
|
||||
expect(result!.confidence).toBeGreaterThanOrEqual(0.60)
|
||||
})
|
||||
|
||||
it('returns null when amount is too different', async () => {
|
||||
const item = makeInvoiceInboxItem({
|
||||
document_type: 'receipt',
|
||||
status: 'ready',
|
||||
extracted_data: receiptExtraction as unknown as Record<string, unknown>,
|
||||
})
|
||||
const tx = makeTransaction({
|
||||
amount: -500,
|
||||
date: '2024-06-15',
|
||||
merchant_name: 'ICA Maxi',
|
||||
})
|
||||
|
||||
const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
|
||||
expect(result).toBeNull()
|
||||
})
|
||||
|
||||
it('returns null when date is too far away', async () => {
|
||||
const item = makeInvoiceInboxItem({
|
||||
document_type: 'receipt',
|
||||
status: 'ready',
|
||||
extracted_data: receiptExtraction as unknown as Record<string, unknown>,
|
||||
})
|
||||
const tx = makeTransaction({
|
||||
amount: -299,
|
||||
date: '2024-06-25', // 10 days after
|
||||
merchant_name: 'ICA Maxi',
|
||||
})
|
||||
|
||||
const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
|
||||
expect(result).toBeNull()
|
||||
})
|
||||
|
||||
it('skips transactions with existing receipt_id', async () => {
|
||||
const item = makeInvoiceInboxItem({
|
||||
document_type: 'receipt',
|
||||
status: 'ready',
|
||||
extracted_data: receiptExtraction as unknown as Record<string, unknown>,
|
||||
})
|
||||
const tx = makeTransaction({
|
||||
amount: -299,
|
||||
date: '2024-06-15',
|
||||
merchant_name: 'ICA Maxi',
|
||||
receipt_id: 'existing-receipt',
|
||||
})
|
||||
|
||||
const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
|
||||
expect(result).toBeNull()
|
||||
})
|
||||
|
||||
it('returns null when total is 0 or null', async () => {
|
||||
const zeroExtraction = {
|
||||
...receiptExtraction,
|
||||
totals: { ...receiptExtraction.totals, total: 0 },
|
||||
}
|
||||
const item = makeInvoiceInboxItem({
|
||||
document_type: 'receipt',
|
||||
status: 'ready',
|
||||
extracted_data: zeroExtraction as unknown as Record<string, unknown>,
|
||||
})
|
||||
const tx = makeTransaction({ amount: -299, date: '2024-06-15' })
|
||||
|
||||
const result = await matchDocumentToTransactions(mockSupabase, 'user-1', item, [tx])
|
||||
expect(result).toBeNull()
|
||||
})
|
||||
})
|
||||
})
|
||||
@@ -0,0 +1,127 @@
|
||||
/**
|
||||
* Batch Document Matching
|
||||
*
|
||||
* Orchestrates matching multiple inbox items to transactions in a single sweep.
|
||||
* Fetches all unbooked transactions once, then runs per-item matching with
|
||||
* greedy assignment to prevent double-matching.
|
||||
*/
|
||||
|
||||
import type { SupabaseClient } from '@supabase/supabase-js'
|
||||
import type { InvoiceInboxItem, Transaction } from '@/types'
|
||||
import { matchDocumentToTransactions, type DocumentMatchResult } from './document-matcher'
|
||||
|
||||
export interface BatchMatchResult {
|
||||
matched: number
|
||||
total: number
|
||||
matches: Array<{ inboxItemId: string; result: DocumentMatchResult }>
|
||||
}
|
||||
|
||||
/**
|
||||
* Run a matching sweep for all ready unmatched inbox items.
|
||||
*
|
||||
* 1. Fetches all ready/processing inbox items without a matched_transaction_id
|
||||
* 2. Fetches all unbooked expense transactions
|
||||
* 3. Runs matching per item, greedily assigning (highest confidence first)
|
||||
* 4. Persists matches back to inbox items
|
||||
*/
|
||||
export async function runDocumentMatchingSweep(
|
||||
supabase: SupabaseClient,
|
||||
userId: string,
|
||||
inboxItemIds?: string[]
|
||||
): Promise<BatchMatchResult> {
|
||||
// 1. Fetch unmatched inbox items
|
||||
let query = supabase
|
||||
.from('invoice_inbox_items')
|
||||
.select('*')
|
||||
.eq('user_id', userId)
|
||||
.is('matched_transaction_id', null)
|
||||
.in('status', ['ready', 'processing'])
|
||||
|
||||
if (inboxItemIds && inboxItemIds.length > 0) {
|
||||
query = query.in('id', inboxItemIds)
|
||||
}
|
||||
|
||||
const { data: inboxItems, error: itemsError } = await query
|
||||
|
||||
if (itemsError || !inboxItems || inboxItems.length === 0) {
|
||||
console.log(`[batch-match] No unmatched inbox items found`)
|
||||
return { matched: 0, total: 0, matches: [] }
|
||||
}
|
||||
|
||||
console.log(`[batch-match] Starting sweep: ${inboxItems.length} unmatched inbox items`)
|
||||
|
||||
// 2. Fetch all unbooked expense transactions (broad window: last 90 days)
|
||||
const ninetyDaysAgo = new Date()
|
||||
ninetyDaysAgo.setDate(ninetyDaysAgo.getDate() - 90)
|
||||
|
||||
const { data: transactions, error: txError } = await supabase
|
||||
.from('transactions')
|
||||
.select('*')
|
||||
.eq('user_id', userId)
|
||||
.is('journal_entry_id', null)
|
||||
.is('is_business', null)
|
||||
.lt('amount', 0)
|
||||
.gte('date', ninetyDaysAgo.toISOString().split('T')[0])
|
||||
.order('date', { ascending: false })
|
||||
|
||||
if (txError || !transactions || transactions.length === 0) {
|
||||
console.log(`[batch-match] No candidate transactions found (last 90 days)`)
|
||||
return { matched: 0, total: inboxItems.length, matches: [] }
|
||||
}
|
||||
|
||||
console.log(`[batch-match] ${transactions.length} candidate transactions (last 90 days)`)
|
||||
|
||||
// 3. Run matching for each item and collect results
|
||||
const pendingMatches: Array<{
|
||||
inboxItemId: string
|
||||
result: DocumentMatchResult
|
||||
}> = []
|
||||
|
||||
for (const item of inboxItems as InvoiceInboxItem[]) {
|
||||
const result = await matchDocumentToTransactions(
|
||||
supabase,
|
||||
userId,
|
||||
item,
|
||||
transactions as Transaction[]
|
||||
)
|
||||
if (result) {
|
||||
pendingMatches.push({ inboxItemId: item.id, result })
|
||||
}
|
||||
}
|
||||
|
||||
// 4. Greedy assignment: sort by confidence desc, assign each transaction at most once
|
||||
pendingMatches.sort((a, b) => b.result.confidence - a.result.confidence)
|
||||
|
||||
const assignedTransactionIds = new Set<string>()
|
||||
const finalMatches: typeof pendingMatches = []
|
||||
|
||||
for (const match of pendingMatches) {
|
||||
if (assignedTransactionIds.has(match.result.transactionId)) {
|
||||
console.log(`[batch-match] Skipped item=${match.inboxItemId} → tx=${match.result.transactionId} (already assigned to higher-confidence match)`)
|
||||
continue // Transaction already assigned to a higher-confidence match
|
||||
}
|
||||
assignedTransactionIds.add(match.result.transactionId)
|
||||
finalMatches.push(match)
|
||||
}
|
||||
|
||||
console.log(`[batch-match] Sweep complete: ${finalMatches.length}/${inboxItems.length} items matched, ${pendingMatches.length - finalMatches.length} skipped (greedy dedup)`)
|
||||
|
||||
// 5. Persist matches
|
||||
for (const { inboxItemId, result } of finalMatches) {
|
||||
await supabase
|
||||
.from('invoice_inbox_items')
|
||||
.update({
|
||||
matched_transaction_id: result.transactionId,
|
||||
match_confidence: result.confidence,
|
||||
match_method: result.method,
|
||||
})
|
||||
.eq('id', inboxItemId)
|
||||
.eq('user_id', userId)
|
||||
}
|
||||
|
||||
return {
|
||||
matched: finalMatches.length,
|
||||
total: inboxItems.length,
|
||||
matches: finalMatches,
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,164 @@
|
||||
/**
|
||||
* Document Classifier using Claude Haiku Vision API
|
||||
*
|
||||
* SERVER-ONLY: This module uses the Anthropic SDK and must only be imported
|
||||
* in server components or API routes.
|
||||
*
|
||||
* Classifies documents as supplier invoices, receipts, government letters,
|
||||
* or unknown. Also detects EU reverse charge for supplier invoices.
|
||||
*/
|
||||
|
||||
import 'server-only'
|
||||
import Anthropic from '@anthropic-ai/sdk'
|
||||
import type { DocumentClassificationType } from '@/types'
|
||||
|
||||
const anthropic = new Anthropic()
|
||||
|
||||
const MAX_RETRIES = 3
|
||||
const RETRY_DELAY_MS = 1000
|
||||
|
||||
type ImageMediaType = 'image/jpeg' | 'image/png' | 'image/webp' | 'image/gif'
|
||||
|
||||
export interface DocumentClassification {
|
||||
type: DocumentClassificationType
|
||||
confidence: number
|
||||
reasoning: string
|
||||
isReverseCharge?: boolean
|
||||
}
|
||||
|
||||
/**
|
||||
* Classify a document using Claude Haiku Vision.
|
||||
* Determines if it's a supplier invoice, receipt, government letter, or unknown.
|
||||
*/
|
||||
export async function classifyDocument(
|
||||
base64: string,
|
||||
mimeType: string
|
||||
): Promise<DocumentClassification> {
|
||||
const systemPrompt = `Du är expert på att klassificera svenska affärsdokument.
|
||||
Din uppgift är att avgöra vilken typ av dokument som visas.
|
||||
|
||||
DOKUMENTTYPER:
|
||||
- supplier_invoice: Leverantörsfaktura (har fakturanummer, bankgiro/plusgiro, förfallodatum, leverantörsuppgifter)
|
||||
- receipt: Kvitto (butiks-/restaurangkvitto, kort betalningsbevis med artikelrader)
|
||||
- government_letter: Myndighetspost (från Skatteverket, Bolagsverket, Försäkringskassan, kommun, etc.)
|
||||
- unknown: Annat dokument som inte passar ovan
|
||||
|
||||
FÖR LEVERANTÖRSFAKTUROR - kontrollera även:
|
||||
- Är fakturan från en utländsk/EU-leverantör utan svensk moms?
|
||||
- Nämner dokumentet "reverse charge", "omvänd skattskyldighet", eller "artikel 196"?
|
||||
- Har leverantören ett VAT-nummer som INTE börjar med SE?
|
||||
Om ja: flagga isReverseCharge = true`
|
||||
|
||||
const userPrompt = `Klassificera detta dokument. Returnera ENDAST ett JSON-objekt:
|
||||
|
||||
{
|
||||
"type": "supplier_invoice" | "receipt" | "government_letter" | "unknown",
|
||||
"confidence": 0.95,
|
||||
"reasoning": "Kort förklaring",
|
||||
"isReverseCharge": false
|
||||
}
|
||||
|
||||
Returnera ENDAST JSON-objektet, ingen annan text.`
|
||||
|
||||
const isPdf = mimeType === 'application/pdf'
|
||||
const isImage = mimeType.startsWith('image/')
|
||||
|
||||
if (!isPdf && !isImage) {
|
||||
throw new Error(`Unsupported file type: ${mimeType}`)
|
||||
}
|
||||
|
||||
let lastError: Error | null = null
|
||||
|
||||
for (let attempt = 0; attempt < MAX_RETRIES; attempt++) {
|
||||
try {
|
||||
const contentBlocks: Anthropic.MessageCreateParams['messages'][0]['content'] = isPdf
|
||||
? [
|
||||
{
|
||||
type: 'document' as const,
|
||||
source: {
|
||||
type: 'base64' as const,
|
||||
media_type: 'application/pdf' as const,
|
||||
data: base64,
|
||||
},
|
||||
},
|
||||
{ type: 'text' as const, text: userPrompt },
|
||||
]
|
||||
: [
|
||||
{
|
||||
type: 'image' as const,
|
||||
source: {
|
||||
type: 'base64' as const,
|
||||
media_type: mimeType as ImageMediaType,
|
||||
data: base64,
|
||||
},
|
||||
},
|
||||
{ type: 'text' as const, text: userPrompt },
|
||||
]
|
||||
|
||||
const message = await anthropic.messages.create({
|
||||
model: 'claude-haiku-4-5-20251001',
|
||||
max_tokens: 1024,
|
||||
messages: [{ role: 'user', content: contentBlocks }],
|
||||
system: systemPrompt,
|
||||
})
|
||||
|
||||
const content = message.content[0]
|
||||
if (content.type !== 'text') {
|
||||
throw new Error('Unexpected response type from AI')
|
||||
}
|
||||
|
||||
let jsonText = content.text.trim()
|
||||
if (jsonText.startsWith('```json')) {
|
||||
jsonText = jsonText.slice(7)
|
||||
} else if (jsonText.startsWith('```')) {
|
||||
jsonText = jsonText.slice(3)
|
||||
}
|
||||
if (jsonText.endsWith('```')) {
|
||||
jsonText = jsonText.slice(0, -3)
|
||||
}
|
||||
jsonText = jsonText.trim()
|
||||
|
||||
const parsed = JSON.parse(jsonText)
|
||||
return validateClassification(parsed)
|
||||
} catch (error) {
|
||||
lastError = error instanceof Error ? error : new Error('Unknown error')
|
||||
|
||||
if (error instanceof SyntaxError) {
|
||||
throw new Error(`Failed to parse AI response: ${lastError.message}`)
|
||||
}
|
||||
|
||||
if (attempt < MAX_RETRIES - 1) {
|
||||
await sleep(RETRY_DELAY_MS * (attempt + 1))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
throw new Error(`Document classification failed after ${MAX_RETRIES} attempts: ${lastError?.message}`)
|
||||
}
|
||||
|
||||
const VALID_TYPES: DocumentClassificationType[] = [
|
||||
'supplier_invoice',
|
||||
'receipt',
|
||||
'government_letter',
|
||||
'unknown',
|
||||
]
|
||||
|
||||
function validateClassification(raw: unknown): DocumentClassification {
|
||||
if (!raw || typeof raw !== 'object') {
|
||||
throw new Error('Invalid classification result: not an object')
|
||||
}
|
||||
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
const data = raw as any
|
||||
|
||||
const type = VALID_TYPES.includes(data.type) ? data.type : 'unknown'
|
||||
const confidence = typeof data.confidence === 'number' ? data.confidence : 0.5
|
||||
const reasoning = typeof data.reasoning === 'string' ? data.reasoning : ''
|
||||
const isReverseCharge = type === 'supplier_invoice' ? Boolean(data.isReverseCharge) : undefined
|
||||
|
||||
return { type, confidence, reasoning, isReverseCharge }
|
||||
}
|
||||
|
||||
function sleep(ms: number): Promise<void> {
|
||||
return new Promise((resolve) => setTimeout(resolve, ms))
|
||||
}
|
||||
@@ -0,0 +1,139 @@
|
||||
/**
|
||||
* Core Receipt Matcher — pure matching utility functions extracted from the
|
||||
* receipt-ocr extension so they can be reused by the document matching engine.
|
||||
*
|
||||
* These are pure functions with no Supabase or extension dependencies.
|
||||
*/
|
||||
|
||||
// Matching configuration (re-exported for consumers)
|
||||
export const DATE_TOLERANCE_DAYS = 3
|
||||
export const AMOUNT_TOLERANCE_PERCENT = 0.05
|
||||
export const MIN_MATCH_CONFIDENCE = 0.4
|
||||
|
||||
/**
|
||||
* Normalize a merchant name for comparison.
|
||||
* Removes special characters, Swedish company suffixes, and extra whitespace.
|
||||
*/
|
||||
export function normalizeMerchantName(name: string): string {
|
||||
return name
|
||||
.toLowerCase()
|
||||
.replace(/[^\w\såäöé]/g, '') // Remove special chars except Swedish letters
|
||||
.replace(/\b(ab|hb|kb|ek|för|stiftelse)\b/g, '') // Remove company suffixes
|
||||
.replace(/\s+/g, ' ')
|
||||
.trim()
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate Levenshtein (edit) distance between two strings.
|
||||
*/
|
||||
export function levenshteinDistance(str1: string, str2: string): number {
|
||||
const m = str1.length
|
||||
const n = str2.length
|
||||
|
||||
const dp: number[][] = Array(m + 1)
|
||||
.fill(null)
|
||||
.map(() => Array(n + 1).fill(0))
|
||||
|
||||
for (let i = 0; i <= m; i++) dp[i][0] = i
|
||||
for (let j = 0; j <= n; j++) dp[0][j] = j
|
||||
|
||||
for (let i = 1; i <= m; i++) {
|
||||
for (let j = 1; j <= n; j++) {
|
||||
const cost = str1[i - 1] === str2[j - 1] ? 0 : 1
|
||||
dp[i][j] = Math.min(
|
||||
dp[i - 1][j] + 1, // deletion
|
||||
dp[i][j - 1] + 1, // insertion
|
||||
dp[i - 1][j - 1] + cost // substitution
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
return dp[m][n]
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate merchant name similarity using Levenshtein distance and word overlap.
|
||||
* Returns a value between 0 (no match) and 1 (exact match).
|
||||
*/
|
||||
export function calculateMerchantSimilarity(name1: string, name2: string): number {
|
||||
if (!name1 || !name2) return 0
|
||||
|
||||
const n1 = normalizeMerchantName(name1)
|
||||
const n2 = normalizeMerchantName(name2)
|
||||
|
||||
// Exact match
|
||||
if (n1 === n2) return 1
|
||||
|
||||
// One contains the other
|
||||
if (n1.includes(n2) || n2.includes(n1)) return 0.9
|
||||
|
||||
// Word overlap
|
||||
const words1 = n1.split(/\s+/)
|
||||
const words2 = n2.split(/\s+/)
|
||||
const commonWords = words1.filter((w) => words2.includes(w))
|
||||
|
||||
if (commonWords.length > 0) {
|
||||
const overlapScore = commonWords.length / Math.max(words1.length, words2.length)
|
||||
if (overlapScore >= 0.5) return 0.7 + overlapScore * 0.2
|
||||
}
|
||||
|
||||
// Levenshtein similarity
|
||||
const distance = levenshteinDistance(n1, n2)
|
||||
const maxLength = Math.max(n1.length, n2.length)
|
||||
return 1 - distance / maxLength
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate a weighted match confidence score from date, amount, and merchant signals.
|
||||
* Weights: amount 40%, merchant 35%, date 25%.
|
||||
*
|
||||
* When merchant similarity is 0, the merchant weight is excluded from the
|
||||
* total weight so the confidence is normalized across the active signals only.
|
||||
*/
|
||||
export function calculateMatchConfidence(
|
||||
dateVariance: number,
|
||||
amountVariance: number,
|
||||
merchantSimilarity: number,
|
||||
dateTolerance: number = DATE_TOLERANCE_DAYS,
|
||||
amountTolerance: number = AMOUNT_TOLERANCE_PERCENT
|
||||
): { confidence: number; matchReasons: string[] } {
|
||||
const matchReasons: string[] = []
|
||||
let totalWeight = 0
|
||||
let weightedScore = 0
|
||||
|
||||
// Date score (weight: 25%)
|
||||
const dateScore = Math.max(0, 1 - dateVariance / dateTolerance)
|
||||
if (dateScore >= 0.8) {
|
||||
matchReasons.push(dateVariance === 0 ? 'Exakt datum' : `Datum ±${Math.round(dateVariance)} dagar`)
|
||||
}
|
||||
weightedScore += dateScore * 0.25
|
||||
totalWeight += 0.25
|
||||
|
||||
// Amount score (weight: 40%)
|
||||
const amountScore = Math.max(0, 1 - amountVariance / amountTolerance)
|
||||
if (amountVariance < 0.01) {
|
||||
matchReasons.push('Exakt belopp')
|
||||
} else if (amountVariance < amountTolerance) {
|
||||
matchReasons.push(`Belopp ±${Math.round(amountVariance * 100)}%`)
|
||||
}
|
||||
weightedScore += amountScore * 0.4
|
||||
totalWeight += 0.4
|
||||
|
||||
// Merchant score (weight: 35%) — only counted when there's data
|
||||
if (merchantSimilarity > 0) {
|
||||
if (merchantSimilarity >= 0.9) {
|
||||
matchReasons.push('Handlare matchar')
|
||||
} else if (merchantSimilarity >= 0.6) {
|
||||
matchReasons.push('Trolig handlarmatch')
|
||||
}
|
||||
weightedScore += merchantSimilarity * 0.35
|
||||
totalWeight += 0.35
|
||||
}
|
||||
|
||||
const confidence = totalWeight > 0 ? weightedScore / totalWeight : 0
|
||||
|
||||
return {
|
||||
confidence: Math.round(confidence * 100) / 100,
|
||||
matchReasons,
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,322 @@
|
||||
/**
|
||||
* Document-to-Transaction Matcher
|
||||
*
|
||||
* Pure matching logic that works from extracted data already stored on inbox items.
|
||||
* Zero AI or extension dependencies — works entirely from structured data.
|
||||
*
|
||||
* Matching passes by document type:
|
||||
*
|
||||
* Supplier invoices:
|
||||
* 1. Payment reference exact match → 0.98
|
||||
* 2. Exact amount + bankgiro → 0.92
|
||||
* 3. Exact amount + date ±5 days → 0.85
|
||||
* 4. Fuzzy amount + supplier name → 0.70
|
||||
*
|
||||
* Receipts:
|
||||
* Weighted scoring (amount 40%, date 25%, merchant 35%), min confidence 0.60
|
||||
*/
|
||||
|
||||
import type { SupabaseClient } from '@supabase/supabase-js'
|
||||
import type { InvoiceInboxItem, Transaction, InvoiceExtractionResult, ReceiptExtractionResult } from '@/types'
|
||||
import {
|
||||
calculateMerchantSimilarity,
|
||||
calculateMatchConfidence,
|
||||
} from './core-receipt-matcher'
|
||||
|
||||
export type DocumentMatchMethod =
|
||||
| 'payment_reference'
|
||||
| 'amount_date'
|
||||
| 'amount_merchant'
|
||||
| 'receipt_match'
|
||||
|
||||
export interface DocumentMatchResult {
|
||||
transactionId: string
|
||||
confidence: number
|
||||
method: DocumentMatchMethod
|
||||
matchReasons: string[]
|
||||
}
|
||||
|
||||
/**
|
||||
* Match a single inbox item to the best candidate transaction.
|
||||
*
|
||||
* If `candidateTransactions` is not provided, fetches unbooked expense
|
||||
* transactions within ±7 days of the document date.
|
||||
*/
|
||||
export async function matchDocumentToTransactions(
|
||||
supabase: SupabaseClient,
|
||||
userId: string,
|
||||
inboxItem: InvoiceInboxItem,
|
||||
candidateTransactions?: Transaction[]
|
||||
): Promise<DocumentMatchResult | null> {
|
||||
const tag = `[document-matcher] item=${inboxItem.id} type=${inboxItem.document_type}`
|
||||
|
||||
// Only match supplier invoices and receipts
|
||||
if (inboxItem.document_type === 'government_letter' || inboxItem.document_type === 'unknown') {
|
||||
console.log(`${tag} — skipped (unsupported document type)`)
|
||||
return null
|
||||
}
|
||||
|
||||
if (!inboxItem.extracted_data) {
|
||||
console.log(`${tag} — skipped (no extracted_data)`)
|
||||
return null
|
||||
}
|
||||
|
||||
const transactions = candidateTransactions ?? (await fetchCandidateTransactions(supabase, userId, inboxItem))
|
||||
|
||||
console.log(`${tag} — ${transactions.length} candidate transactions`)
|
||||
|
||||
if (transactions.length === 0) {
|
||||
console.log(`${tag} — no candidates, aborting`)
|
||||
return null
|
||||
}
|
||||
|
||||
let result: DocumentMatchResult | null = null
|
||||
|
||||
if (inboxItem.document_type === 'supplier_invoice') {
|
||||
result = matchSupplierInvoiceDocument(inboxItem, transactions)
|
||||
} else if (inboxItem.document_type === 'receipt') {
|
||||
result = matchReceiptDocument(inboxItem, transactions)
|
||||
}
|
||||
|
||||
if (result) {
|
||||
console.log(`${tag} — MATCHED tx=${result.transactionId} confidence=${result.confidence} method=${result.method} reasons=[${result.matchReasons.join(', ')}]`)
|
||||
} else {
|
||||
console.log(`${tag} — no match found`)
|
||||
}
|
||||
|
||||
return result
|
||||
}
|
||||
|
||||
/**
|
||||
* Fetch unbooked expense transactions within ±7 days of the document date.
|
||||
*/
|
||||
async function fetchCandidateTransactions(
|
||||
supabase: SupabaseClient,
|
||||
userId: string,
|
||||
inboxItem: InvoiceInboxItem
|
||||
): Promise<Transaction[]> {
|
||||
const docDate = getDocumentDate(inboxItem)
|
||||
if (!docDate) return []
|
||||
|
||||
const startDate = new Date(docDate)
|
||||
startDate.setDate(startDate.getDate() - 7)
|
||||
const endDate = new Date(docDate)
|
||||
endDate.setDate(endDate.getDate() + 7)
|
||||
|
||||
const { data, error } = await supabase
|
||||
.from('transactions')
|
||||
.select('*')
|
||||
.eq('user_id', userId)
|
||||
.is('journal_entry_id', null)
|
||||
.is('is_business', null)
|
||||
.lt('amount', 0)
|
||||
.gte('date', startDate.toISOString().split('T')[0])
|
||||
.lte('date', endDate.toISOString().split('T')[0])
|
||||
.order('date', { ascending: false })
|
||||
|
||||
if (error || !data) return []
|
||||
return data as Transaction[]
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract the most relevant date from an inbox item's extracted data.
|
||||
*/
|
||||
function getDocumentDate(inboxItem: InvoiceInboxItem): string | null {
|
||||
const data = inboxItem.extracted_data as Record<string, unknown> | null
|
||||
if (!data) return null
|
||||
|
||||
if (inboxItem.document_type === 'supplier_invoice') {
|
||||
const extraction = data as unknown as InvoiceExtractionResult
|
||||
return extraction.invoice?.dueDate ?? extraction.invoice?.invoiceDate ?? null
|
||||
}
|
||||
|
||||
if (inboxItem.document_type === 'receipt') {
|
||||
const extraction = data as unknown as ReceiptExtractionResult
|
||||
return extraction.receipt?.date ?? null
|
||||
}
|
||||
|
||||
return null
|
||||
}
|
||||
|
||||
/**
|
||||
* Match a supplier invoice inbox item to transactions using a 4-pass algorithm.
|
||||
*/
|
||||
function matchSupplierInvoiceDocument(
|
||||
inboxItem: InvoiceInboxItem,
|
||||
transactions: Transaction[]
|
||||
): DocumentMatchResult | null {
|
||||
const tag = `[document-matcher:supplier] item=${inboxItem.id}`
|
||||
const extraction = inboxItem.extracted_data as unknown as InvoiceExtractionResult
|
||||
if (!extraction) return null
|
||||
|
||||
const invoiceTotal = extraction.totals?.total
|
||||
if (invoiceTotal == null || invoiceTotal === 0) {
|
||||
console.log(`${tag} — no invoice total in extracted data`)
|
||||
return null
|
||||
}
|
||||
|
||||
const paymentRef = extraction.invoice?.paymentReference
|
||||
const bankgiro = extraction.supplier?.bankgiro
|
||||
const plusgiro = extraction.supplier?.plusgiro
|
||||
const supplierName = extraction.supplier?.name
|
||||
const dueDate = extraction.invoice?.dueDate ?? extraction.invoice?.invoiceDate
|
||||
|
||||
console.log(`${tag} — extracted: total=${invoiceTotal}, supplier=${supplierName || '?'}, dueDate=${dueDate || '?'}, paymentRef=${paymentRef || '?'}, bankgiro=${bankgiro || '?'}, templateId=${extraction.suggestedTemplateId || '?'}`)
|
||||
|
||||
let bestMatch: DocumentMatchResult | null = null
|
||||
|
||||
for (const tx of transactions) {
|
||||
const txAmount = Math.abs(tx.amount)
|
||||
const txDesc = (tx.description || '').toLowerCase()
|
||||
const txRef = tx.reference || ''
|
||||
|
||||
// Pass 1: Payment reference exact match → 0.98
|
||||
if (paymentRef && txRef) {
|
||||
const normTxRef = txRef.replace(/\D/g, '')
|
||||
const normPayRef = paymentRef.replace(/\D/g, '')
|
||||
if (normTxRef && normPayRef && normTxRef === normPayRef) {
|
||||
console.log(`${tag} — Pass 1 HIT: tx=${tx.id} ref=${normPayRef}`)
|
||||
return {
|
||||
transactionId: tx.id,
|
||||
confidence: 0.98,
|
||||
method: 'payment_reference',
|
||||
matchReasons: ['Betalningsreferens matchar'],
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Pass 2: Exact amount + bankgiro/plusgiro → 0.92
|
||||
const amountMatch = Math.abs(txAmount - invoiceTotal) < 0.005
|
||||
if (amountMatch) {
|
||||
const bgNorm = bankgiro?.replace(/\D/g, '')
|
||||
const pgNorm = plusgiro?.replace(/\D/g, '')
|
||||
const hasBgMatch = bgNorm && txDesc.includes(bgNorm)
|
||||
const hasPgMatch = pgNorm && txDesc.includes(pgNorm)
|
||||
|
||||
if (hasBgMatch || hasPgMatch) {
|
||||
console.log(`${tag} — Pass 2 HIT: tx=${tx.id} amount=${txAmount} bg/pg match`)
|
||||
return {
|
||||
transactionId: tx.id,
|
||||
confidence: 0.92,
|
||||
method: 'payment_reference',
|
||||
matchReasons: ['Exakt belopp', hasBgMatch ? 'Bankgiro matchar' : 'Plusgiro matchar'],
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Pass 3: Exact amount + date ±14 days → 0.85 (close) / 0.75 (wider)
|
||||
// Invoices are often paid early or a few days late, so we use a 14-day window.
|
||||
if (amountMatch && dueDate) {
|
||||
const txDate = new Date(tx.date)
|
||||
const docDate = new Date(dueDate)
|
||||
const diffDays = Math.abs((txDate.getTime() - docDate.getTime()) / (1000 * 60 * 60 * 24))
|
||||
|
||||
if (diffDays <= 14) {
|
||||
// Higher confidence for close dates, lower for wider window
|
||||
const confidence = diffDays <= 5 ? 0.85 : 0.75
|
||||
console.log(`${tag} — Pass 3 HIT: tx=${tx.id} amount=${txAmount} date_diff=${diffDays.toFixed(1)}d → confidence=${confidence}`)
|
||||
const candidate: DocumentMatchResult = {
|
||||
transactionId: tx.id,
|
||||
confidence,
|
||||
method: 'amount_date',
|
||||
matchReasons: ['Exakt belopp', diffDays === 0 ? 'Exakt datum' : `Datum ±${Math.round(diffDays)} dagar`],
|
||||
}
|
||||
if (!bestMatch || candidate.confidence > bestMatch.confidence) {
|
||||
bestMatch = candidate
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Pass 4: Fuzzy amount (±1%) + supplier name in description → 0.70
|
||||
const fuzzyAmountMatch = Math.abs(txAmount - invoiceTotal) / invoiceTotal <= 0.01
|
||||
if (fuzzyAmountMatch && supplierName) {
|
||||
const normalizedName = supplierName.toLowerCase().replace(/[^\w\såäöé]/g, '')
|
||||
const nameWords = normalizedName.split(/\s+/).filter((w) => w.length >= 3)
|
||||
const nameInDesc = nameWords.some((word) => txDesc.includes(word))
|
||||
|
||||
if (nameInDesc) {
|
||||
console.log(`${tag} — Pass 4 HIT: tx=${tx.id} amount=${txAmount} (~${((Math.abs(txAmount - invoiceTotal) / invoiceTotal) * 100).toFixed(1)}%) name words=[${nameWords.join(',')}]`)
|
||||
const candidate: DocumentMatchResult = {
|
||||
transactionId: tx.id,
|
||||
confidence: 0.70,
|
||||
method: 'amount_merchant',
|
||||
matchReasons: ['Belopp matchar (±1%)', 'Leverantörsnamn i beskrivning'],
|
||||
}
|
||||
if (!bestMatch || candidate.confidence > bestMatch.confidence) {
|
||||
bestMatch = candidate
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return bestMatch
|
||||
}
|
||||
|
||||
/**
|
||||
* Match a receipt inbox item to transactions using weighted scoring.
|
||||
* Weights: amount 40%, date 25%, merchant 35%. Min confidence: 0.60.
|
||||
*/
|
||||
function matchReceiptDocument(
|
||||
inboxItem: InvoiceInboxItem,
|
||||
transactions: Transaction[]
|
||||
): DocumentMatchResult | null {
|
||||
const tag = `[document-matcher:receipt] item=${inboxItem.id}`
|
||||
const extraction = inboxItem.extracted_data as unknown as ReceiptExtractionResult
|
||||
if (!extraction) return null
|
||||
|
||||
const receiptTotal = extraction.totals?.total
|
||||
const receiptDate = extraction.receipt?.date
|
||||
const merchantName = extraction.merchant?.name
|
||||
|
||||
if (receiptTotal == null || receiptTotal === 0) {
|
||||
console.log(`${tag} — no receipt total in extracted data`)
|
||||
return null
|
||||
}
|
||||
|
||||
console.log(`${tag} — extracted: total=${receiptTotal}, date=${receiptDate || '?'}, merchant=${merchantName || '?'}, templateId=${extraction.suggestedTemplateId || '?'}`)
|
||||
|
||||
let bestMatch: DocumentMatchResult | null = null
|
||||
|
||||
for (const tx of transactions) {
|
||||
if (tx.receipt_id) continue // Skip already matched
|
||||
|
||||
const txAmount = Math.abs(tx.amount)
|
||||
const txDate = new Date(tx.date)
|
||||
|
||||
// Calculate date variance
|
||||
const dateVariance = receiptDate
|
||||
? Math.abs((new Date(receiptDate).getTime() - txDate.getTime()) / (1000 * 60 * 60 * 24))
|
||||
: 3 // Default to tolerance boundary if no date
|
||||
|
||||
if (dateVariance > 3) continue
|
||||
|
||||
// Calculate amount variance
|
||||
const amountVariance = Math.abs(receiptTotal - txAmount) / receiptTotal
|
||||
if (amountVariance > 0.05) continue // Skip if >5% off
|
||||
|
||||
// Calculate merchant similarity
|
||||
const txMerchant = tx.merchant_name || tx.description || ''
|
||||
const merchantSimilarity = merchantName
|
||||
? calculateMerchantSimilarity(merchantName, txMerchant)
|
||||
: 0
|
||||
|
||||
const { confidence, matchReasons } = calculateMatchConfidence(
|
||||
dateVariance,
|
||||
amountVariance,
|
||||
merchantSimilarity
|
||||
)
|
||||
|
||||
console.log(`${tag} — scoring tx=${tx.id} "${tx.description}": date_var=${dateVariance.toFixed(1)}d amount_var=${(amountVariance * 100).toFixed(1)}% merchant_sim=${merchantSimilarity.toFixed(2)} → confidence=${confidence}`)
|
||||
|
||||
if (confidence >= 0.60 && (!bestMatch || confidence > bestMatch.confidence)) {
|
||||
bestMatch = {
|
||||
transactionId: tx.id,
|
||||
confidence,
|
||||
method: 'receipt_match',
|
||||
matchReasons,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return bestMatch
|
||||
}
|
||||
Reference in New Issue
Block a user