update
This commit is contained in:
584
test/test.invoices.nanonets.ts
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584
test/test.invoices.nanonets.ts
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/**
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* Invoice extraction using Nanonets-OCR-s + Qwen3 (two-stage pipeline)
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*
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* Stage 1: Nanonets-OCR-s converts document pages to markdown (its strength)
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* Stage 2: Qwen3 extracts structured JSON from the combined markdown
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*
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* This leverages each model's strengths:
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* - Nanonets: Document OCR with semantic tags
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* - Qwen3: Text understanding and JSON extraction
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*/
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import { tap, expect } from '@git.zone/tstest/tapbundle';
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import * as fs from 'fs';
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import * as path from 'path';
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import { execSync } from 'child_process';
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import * as os from 'os';
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import { ensureNanonetsOcr, ensureMiniCpm } from './helpers/docker.js';
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const NANONETS_URL = 'http://localhost:8000/v1';
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const NANONETS_MODEL = 'nanonets/Nanonets-OCR-s';
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const OLLAMA_URL = 'http://localhost:11434';
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const QWEN_MODEL = 'qwen3:8b';
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interface IInvoice {
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invoice_number: string;
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invoice_date: string;
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vendor_name: string;
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currency: string;
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net_amount: number;
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vat_amount: number;
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total_amount: number;
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}
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// Nanonets-specific prompt for document OCR to markdown
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const NANONETS_OCR_PROMPT = `Extract the text from the above document as if you were reading it naturally.
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Return the tables in html format.
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Return the equations in LaTeX representation.
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If there is an image in the document and image caption is not present, add a small description inside <img></img> tag.
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Watermarks should be wrapped in brackets. Ex: <watermark>OFFICIAL COPY</watermark>.
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Page numbers should be wrapped in brackets. Ex: <page_number>14</page_number>.`;
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// JSON extraction prompt for Qwen3
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const JSON_EXTRACTION_PROMPT = `You are an invoice data extractor. Below is an invoice document converted to text/markdown. Extract the key invoice fields as JSON.
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IMPORTANT RULES:
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1. invoice_number: The unique invoice/document number (NOT VAT ID, NOT customer ID)
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2. invoice_date: Format as YYYY-MM-DD
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3. vendor_name: The company that issued the invoice
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4. currency: EUR, USD, or GBP
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5. net_amount: Amount before tax
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6. vat_amount: Tax/VAT amount
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7. total_amount: Final total (gross amount)
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Return ONLY this JSON format, no explanation:
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{
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"invoice_number": "INV-2024-001",
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"invoice_date": "2024-01-15",
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"vendor_name": "Company Name",
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"currency": "EUR",
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"net_amount": 100.00,
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"vat_amount": 19.00,
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"total_amount": 119.00
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}
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INVOICE TEXT:
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`;
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/**
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* Convert PDF to PNG images using ImageMagick
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*/
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function convertPdfToImages(pdfPath: string): string[] {
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const tempDir = fs.mkdtempSync(path.join(os.tmpdir(), 'pdf-convert-'));
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const outputPattern = path.join(tempDir, 'page-%d.png');
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try {
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// Use 150 DPI to keep images within model's context length
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execSync(
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`convert -density 150 -quality 90 "${pdfPath}" -background white -alpha remove "${outputPattern}"`,
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{ stdio: 'pipe' }
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);
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const files = fs.readdirSync(tempDir).filter((f) => f.endsWith('.png')).sort();
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const images: string[] = [];
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for (const file of files) {
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const imagePath = path.join(tempDir, file);
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const imageData = fs.readFileSync(imagePath);
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images.push(imageData.toString('base64'));
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}
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return images;
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} finally {
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fs.rmSync(tempDir, { recursive: true, force: true });
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}
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}
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/**
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* Stage 1: Convert a single page to markdown using Nanonets-OCR-s
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*/
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async function convertPageToMarkdown(image: string, pageNum: number): Promise<string> {
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console.log(` [Nanonets] Converting page ${pageNum} to markdown...`);
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const startTime = Date.now();
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const response = await fetch(`${NANONETS_URL}/chat/completions`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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'Authorization': 'Bearer dummy',
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},
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body: JSON.stringify({
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model: NANONETS_MODEL,
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messages: [{
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role: 'user',
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content: [
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{ type: 'image_url', image_url: { url: `data:image/png;base64,${image}` }},
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{ type: 'text', text: NANONETS_OCR_PROMPT },
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],
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}],
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max_tokens: 4096,
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temperature: 0.0,
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}),
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});
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const elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
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if (!response.ok) {
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const errorText = await response.text();
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console.log(` [Nanonets] ERROR page ${pageNum}: ${response.status} - ${errorText}`);
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throw new Error(`Nanonets API error: ${response.status}`);
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}
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const data = await response.json();
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const content = (data.choices?.[0]?.message?.content || '').trim();
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console.log(` [Nanonets] Page ${pageNum} converted (${elapsed}s, ${content.length} chars)`);
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return content;
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}
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/**
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* Stage 1: Convert all pages to markdown using Nanonets-OCR-s
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*/
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async function convertDocumentToMarkdown(images: string[]): Promise<string> {
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console.log(` [Stage 1] Converting ${images.length} page(s) to markdown with Nanonets-OCR-s...`);
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const markdownPages: string[] = [];
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for (let i = 0; i < images.length; i++) {
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const markdown = await convertPageToMarkdown(images[i], i + 1);
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markdownPages.push(`--- PAGE ${i + 1} ---\n${markdown}`);
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}
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const fullMarkdown = markdownPages.join('\n\n');
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console.log(` [Stage 1] Complete: ${fullMarkdown.length} chars total`);
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return fullMarkdown;
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}
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/**
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* Ensure Qwen3 model is available
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*/
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async function ensureQwen3(): Promise<boolean> {
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try {
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const response = await fetch(`${OLLAMA_URL}/api/tags`);
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if (response.ok) {
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const data = await response.json();
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const models = data.models || [];
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if (models.some((m: { name: string }) => m.name === QWEN_MODEL)) {
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console.log(` [Ollama] Model available: ${QWEN_MODEL}`);
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return true;
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}
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}
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} catch {
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return false;
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}
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console.log(` [Ollama] Pulling ${QWEN_MODEL}...`);
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const pullResponse = await fetch(`${OLLAMA_URL}/api/pull`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({ name: QWEN_MODEL, stream: false }),
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});
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return pullResponse.ok;
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}
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/**
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* Parse amount from string (handles European format)
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*/
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function parseAmount(s: string | number | undefined): number {
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if (s === undefined || s === null) return 0;
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if (typeof s === 'number') return s;
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const match = s.match(/([\d.,]+)/);
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if (!match) return 0;
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const numStr = match[1];
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// Handle European format: 1.234,56 -> 1234.56
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const normalized = numStr.includes(',') && numStr.indexOf(',') > numStr.lastIndexOf('.')
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? numStr.replace(/\./g, '').replace(',', '.')
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: numStr.replace(/,/g, '');
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return parseFloat(normalized) || 0;
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}
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/**
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* Extract invoice number from potentially verbose response
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*/
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function extractInvoiceNumber(s: string | undefined): string {
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if (!s) return '';
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let clean = s.replace(/\*\*/g, '').replace(/`/g, '').trim();
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const patterns = [
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/\b([A-Z]{2,3}\d{10,})\b/i, // IEE2022006460244
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/\b([A-Z]\d{8,})\b/i, // R0014359508
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/\b(INV[-\s]?\d{4}[-\s]?\d+)\b/i, // INV-2024-001
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/\b(\d{7,})\b/, // 1579087430
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];
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for (const pattern of patterns) {
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const match = clean.match(pattern);
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if (match) return match[1];
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}
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return clean.replace(/[^A-Z0-9-]/gi, '').trim() || clean;
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}
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/**
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* Extract date (YYYY-MM-DD) from response
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*/
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function extractDate(s: string | undefined): string {
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if (!s) return '';
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let clean = s.replace(/\*\*/g, '').replace(/`/g, '').trim();
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const isoMatch = clean.match(/(\d{4}-\d{2}-\d{2})/);
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if (isoMatch) return isoMatch[1];
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// Try DD/MM/YYYY or DD.MM.YYYY
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const dmyMatch = clean.match(/(\d{1,2})[\/.](\d{1,2})[\/.](\d{4})/);
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if (dmyMatch) {
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return `${dmyMatch[3]}-${dmyMatch[2].padStart(2, '0')}-${dmyMatch[1].padStart(2, '0')}`;
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}
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return clean.replace(/[^\d-]/g, '').trim();
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}
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/**
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* Extract currency
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*/
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function extractCurrency(s: string | undefined): string {
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if (!s) return 'EUR';
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const upper = s.toUpperCase();
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if (upper.includes('EUR') || upper.includes('€')) return 'EUR';
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if (upper.includes('USD') || upper.includes('$')) return 'USD';
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if (upper.includes('GBP') || upper.includes('£')) return 'GBP';
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return 'EUR';
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}
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/**
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* Extract JSON from response (handles markdown code blocks)
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*/
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function extractJsonFromResponse(response: string): Record<string, unknown> | null {
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// Remove thinking tags if present (Qwen3 may include <think>...</think>)
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let cleanResponse = response.replace(/<think>[\s\S]*?<\/think>/g, '').trim();
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// Try to find JSON in markdown code block
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const codeBlockMatch = cleanResponse.match(/```(?:json)?\s*([\s\S]*?)```/);
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const jsonStr = codeBlockMatch ? codeBlockMatch[1].trim() : cleanResponse;
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try {
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return JSON.parse(jsonStr);
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} catch {
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// Try to find JSON object pattern
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const jsonMatch = jsonStr.match(/\{[\s\S]*\}/);
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if (jsonMatch) {
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try {
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return JSON.parse(jsonMatch[0]);
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} catch {
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return null;
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}
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}
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return null;
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}
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}
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/**
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* Parse JSON response into IInvoice
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*/
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function parseJsonToInvoice(response: string): IInvoice | null {
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const parsed = extractJsonFromResponse(response);
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if (!parsed) return null;
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return {
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invoice_number: extractInvoiceNumber(String(parsed.invoice_number || '')),
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invoice_date: extractDate(String(parsed.invoice_date || '')),
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vendor_name: String(parsed.vendor_name || '').replace(/\*\*/g, '').replace(/`/g, '').trim(),
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currency: extractCurrency(String(parsed.currency || '')),
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net_amount: parseAmount(parsed.net_amount as string | number),
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vat_amount: parseAmount(parsed.vat_amount as string | number),
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total_amount: parseAmount(parsed.total_amount as string | number),
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};
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}
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/**
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* Stage 2: Extract invoice from markdown using Qwen3
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*/
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async function extractInvoiceFromMarkdown(markdown: string, queryId: string): Promise<IInvoice | null> {
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console.log(` [${queryId}] Sending markdown to ${QWEN_MODEL}...`);
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const startTime = Date.now();
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const response = await fetch(`${OLLAMA_URL}/api/chat`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({
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model: QWEN_MODEL,
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messages: [{
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role: 'user',
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content: JSON_EXTRACTION_PROMPT + markdown,
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}],
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stream: false,
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options: {
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num_predict: 2000,
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temperature: 0.1,
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},
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}),
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});
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const elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
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if (!response.ok) {
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console.log(` [${queryId}] ERROR: ${response.status} (${elapsed}s)`);
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throw new Error(`Ollama API error: ${response.status}`);
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}
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const data = await response.json();
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const content = (data.message?.content || '').trim();
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console.log(` [${queryId}] Response received (${elapsed}s, ${content.length} chars)`);
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return parseJsonToInvoice(content);
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}
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/**
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* Compare two invoices for consensus (key fields must match)
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*/
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function invoicesMatch(a: IInvoice, b: IInvoice): boolean {
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const numMatch = a.invoice_number.toLowerCase() === b.invoice_number.toLowerCase();
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const dateMatch = a.invoice_date === b.invoice_date;
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const totalMatch = Math.abs(a.total_amount - b.total_amount) < 0.02;
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return numMatch && dateMatch && totalMatch;
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}
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/**
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* Stage 2: Extract invoice using Qwen3 with consensus
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*/
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async function extractWithConsensus(markdown: string): Promise<IInvoice> {
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const MAX_ATTEMPTS = 3;
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console.log(` [Stage 2] Extracting invoice with ${QWEN_MODEL} (consensus)...`);
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for (let attempt = 1; attempt <= MAX_ATTEMPTS; attempt++) {
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console.log(`\n [Stage 2] --- Attempt ${attempt}/${MAX_ATTEMPTS} ---`);
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// Extract twice
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const inv1 = await extractInvoiceFromMarkdown(markdown, `A${attempt}Q1`);
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const inv2 = await extractInvoiceFromMarkdown(markdown, `A${attempt}Q2`);
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if (!inv1 || !inv2) {
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console.log(` [Stage 2] Parsing failed, retrying...`);
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continue;
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}
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console.log(` [Stage 2] Q1: ${inv1.invoice_number} | ${inv1.invoice_date} | ${inv1.total_amount} ${inv1.currency}`);
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console.log(` [Stage 2] Q2: ${inv2.invoice_number} | ${inv2.invoice_date} | ${inv2.total_amount} ${inv2.currency}`);
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if (invoicesMatch(inv1, inv2)) {
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console.log(` [Stage 2] CONSENSUS REACHED`);
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return inv2;
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}
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console.log(` [Stage 2] NO CONSENSUS`);
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}
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// Fallback: use last response
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console.log(`\n [Stage 2] === FALLBACK ===`);
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const fallback = await extractInvoiceFromMarkdown(markdown, 'FALLBACK');
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if (fallback) {
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console.log(` [Stage 2] ~ FALLBACK: ${fallback.invoice_number} | ${fallback.invoice_date} | ${fallback.total_amount}`);
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return fallback;
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}
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||||
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||||
// Return empty invoice if all else fails
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return {
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invoice_number: '',
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invoice_date: '',
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vendor_name: '',
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currency: 'EUR',
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net_amount: 0,
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vat_amount: 0,
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total_amount: 0,
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||||
};
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||||
}
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||||
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/**
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* Full pipeline: PDF -> Images -> Markdown -> JSON
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*/
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async function extractInvoice(images: string[]): Promise<IInvoice> {
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// Stage 1: Convert to markdown
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const markdown = await convertDocumentToMarkdown(images);
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// Stage 2: Extract invoice with consensus
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const invoice = await extractWithConsensus(markdown);
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return invoice;
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||||
}
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||||
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||||
/**
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* Normalize date to YYYY-MM-DD
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*/
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||||
function normalizeDate(dateStr: string | null): string {
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if (!dateStr) return '';
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if (/^\d{4}-\d{2}-\d{2}$/.test(dateStr)) return dateStr;
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const monthMap: Record<string, string> = {
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JAN: '01', FEB: '02', MAR: '03', APR: '04', MAY: '05', JUN: '06',
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JUL: '07', AUG: '08', SEP: '09', OCT: '10', NOV: '11', DEC: '12',
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};
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||||
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||||
let match = dateStr.match(/^(\d{1,2})-([A-Z]{3})-(\d{4})$/i);
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if (match) {
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||||
return `${match[3]}-${monthMap[match[2].toUpperCase()] || '01'}-${match[1].padStart(2, '0')}`;
|
||||
}
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||||
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||||
match = dateStr.match(/^(\d{1,2})[\/.](\d{1,2})[\/.](\d{4})$/);
|
||||
if (match) {
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||||
return `${match[3]}-${match[2].padStart(2, '0')}-${match[1].padStart(2, '0')}`;
|
||||
}
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||||
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||||
return dateStr;
|
||||
}
|
||||
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||||
/**
|
||||
* Compare extracted invoice against expected
|
||||
*/
|
||||
function compareInvoice(
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||||
extracted: IInvoice,
|
||||
expected: IInvoice
|
||||
): { match: boolean; errors: string[] } {
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||||
const errors: string[] = [];
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||||
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||||
// Compare invoice number (normalize by removing spaces and case)
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||||
const extNum = extracted.invoice_number?.replace(/\s/g, '').toLowerCase() || '';
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||||
const expNum = expected.invoice_number?.replace(/\s/g, '').toLowerCase() || '';
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||||
if (extNum !== expNum) {
|
||||
errors.push(`invoice_number: expected "${expected.invoice_number}", got "${extracted.invoice_number}"`);
|
||||
}
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||||
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||||
// Compare date
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||||
if (normalizeDate(extracted.invoice_date) !== normalizeDate(expected.invoice_date)) {
|
||||
errors.push(`invoice_date: expected "${expected.invoice_date}", got "${extracted.invoice_date}"`);
|
||||
}
|
||||
|
||||
// Compare total amount (with tolerance)
|
||||
if (Math.abs(extracted.total_amount - expected.total_amount) > 0.02) {
|
||||
errors.push(`total_amount: expected ${expected.total_amount}, got ${extracted.total_amount}`);
|
||||
}
|
||||
|
||||
// Compare currency
|
||||
if (extracted.currency?.toUpperCase() !== expected.currency?.toUpperCase()) {
|
||||
errors.push(`currency: expected "${expected.currency}", got "${extracted.currency}"`);
|
||||
}
|
||||
|
||||
return { match: errors.length === 0, errors };
|
||||
}
|
||||
|
||||
/**
|
||||
* Find all test cases (PDF + JSON pairs) in .nogit/invoices/
|
||||
*/
|
||||
function findTestCases(): Array<{ name: string; pdfPath: string; jsonPath: string }> {
|
||||
const testDir = path.join(process.cwd(), '.nogit/invoices');
|
||||
if (!fs.existsSync(testDir)) {
|
||||
return [];
|
||||
}
|
||||
|
||||
const files = fs.readdirSync(testDir);
|
||||
const pdfFiles = files.filter((f) => f.endsWith('.pdf'));
|
||||
const testCases: Array<{ name: string; pdfPath: string; jsonPath: string }> = [];
|
||||
|
||||
for (const pdf of pdfFiles) {
|
||||
const baseName = pdf.replace('.pdf', '');
|
||||
const jsonFile = `${baseName}.json`;
|
||||
if (files.includes(jsonFile)) {
|
||||
testCases.push({
|
||||
name: baseName,
|
||||
pdfPath: path.join(testDir, pdf),
|
||||
jsonPath: path.join(testDir, jsonFile),
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
testCases.sort((a, b) => a.name.localeCompare(b.name));
|
||||
return testCases;
|
||||
}
|
||||
|
||||
// Tests
|
||||
|
||||
tap.test('setup: ensure containers are running', async () => {
|
||||
console.log('\n[Setup] Checking Docker containers...\n');
|
||||
|
||||
// Nanonets for OCR
|
||||
const nanonetsOk = await ensureNanonetsOcr();
|
||||
expect(nanonetsOk).toBeTrue();
|
||||
|
||||
// Ollama for Qwen3
|
||||
const ollamaOk = await ensureMiniCpm();
|
||||
expect(ollamaOk).toBeTrue();
|
||||
|
||||
// Qwen3 model
|
||||
const qwenOk = await ensureQwen3();
|
||||
expect(qwenOk).toBeTrue();
|
||||
|
||||
console.log('\n[Setup] All containers ready!\n');
|
||||
});
|
||||
|
||||
tap.test('should have models available', async () => {
|
||||
// Check Nanonets
|
||||
const nanonetsResp = await fetch(`${NANONETS_URL}/models`);
|
||||
expect(nanonetsResp.ok).toBeTrue();
|
||||
|
||||
// Check Qwen3
|
||||
const ollamaResp = await fetch(`${OLLAMA_URL}/api/tags`);
|
||||
expect(ollamaResp.ok).toBeTrue();
|
||||
const data = await ollamaResp.json();
|
||||
const modelNames = data.models.map((m: { name: string }) => m.name);
|
||||
expect(modelNames.some((name: string) => name.includes('qwen3'))).toBeTrue();
|
||||
});
|
||||
|
||||
const testCases = findTestCases();
|
||||
console.log(`\nFound ${testCases.length} invoice test cases (Nanonets + Qwen3)\n`);
|
||||
|
||||
let passedCount = 0;
|
||||
let failedCount = 0;
|
||||
const processingTimes: number[] = [];
|
||||
|
||||
for (const testCase of testCases) {
|
||||
tap.test(`should extract invoice: ${testCase.name}`, async () => {
|
||||
const expected: IInvoice = JSON.parse(fs.readFileSync(testCase.jsonPath, 'utf-8'));
|
||||
console.log(`\n=== ${testCase.name} ===`);
|
||||
console.log(`Expected: ${expected.invoice_number} | ${expected.invoice_date} | ${expected.total_amount} ${expected.currency}`);
|
||||
|
||||
const startTime = Date.now();
|
||||
const images = convertPdfToImages(testCase.pdfPath);
|
||||
console.log(` Pages: ${images.length}`);
|
||||
|
||||
const extracted = await extractInvoice(images);
|
||||
console.log(` Extracted: ${extracted.invoice_number} | ${extracted.invoice_date} | ${extracted.total_amount} ${extracted.currency}`);
|
||||
|
||||
const elapsedMs = Date.now() - startTime;
|
||||
processingTimes.push(elapsedMs);
|
||||
|
||||
const result = compareInvoice(extracted, expected);
|
||||
|
||||
if (result.match) {
|
||||
passedCount++;
|
||||
console.log(` Result: MATCH (${(elapsedMs / 1000).toFixed(1)}s)`);
|
||||
} else {
|
||||
failedCount++;
|
||||
console.log(` Result: MISMATCH (${(elapsedMs / 1000).toFixed(1)}s)`);
|
||||
result.errors.forEach((e) => console.log(` - ${e}`));
|
||||
}
|
||||
|
||||
expect(result.match).toBeTrue();
|
||||
});
|
||||
}
|
||||
|
||||
tap.test('summary', async () => {
|
||||
const totalInvoices = testCases.length;
|
||||
const accuracy = totalInvoices > 0 ? (passedCount / totalInvoices) * 100 : 0;
|
||||
const totalTimeMs = processingTimes.reduce((a, b) => a + b, 0);
|
||||
const avgTimeSec = processingTimes.length > 0 ? totalTimeMs / processingTimes.length / 1000 : 0;
|
||||
|
||||
console.log(`\n========================================`);
|
||||
console.log(` Invoice Extraction Summary`);
|
||||
console.log(` (Nanonets + Qwen3 Pipeline)`);
|
||||
console.log(`========================================`);
|
||||
console.log(` Stage 1: Nanonets-OCR-s (doc -> md)`);
|
||||
console.log(` Stage 2: Qwen3 8B (md -> JSON)`);
|
||||
console.log(` Passed: ${passedCount}/${totalInvoices}`);
|
||||
console.log(` Failed: ${failedCount}/${totalInvoices}`);
|
||||
console.log(` Accuracy: ${accuracy.toFixed(1)}%`);
|
||||
console.log(`----------------------------------------`);
|
||||
console.log(` Total time: ${(totalTimeMs / 1000).toFixed(1)}s`);
|
||||
console.log(` Avg per inv: ${avgTimeSec.toFixed(1)}s`);
|
||||
console.log(`========================================\n`);
|
||||
});
|
||||
|
||||
export default tap.start();
|
||||
Reference in New Issue
Block a user