feat(ocr): add PaddleOCR GPU Docker image and FastAPI OCR server with entrypoint; implement OCR endpoints and consensus extraction testing
This commit is contained in:
377
test/test.invoices.ts
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377
test/test.invoices.ts
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@@ -0,0 +1,377 @@
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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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const OLLAMA_URL = 'http://localhost:11434';
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const MODEL = 'openbmb/minicpm-v4.5:q8_0';
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const PADDLEOCR_URL = 'http://localhost:5000';
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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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/**
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* Extract OCR text from an image using PaddleOCR
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*/
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async function extractOcrText(imageBase64: string): Promise<string> {
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const formData = new FormData();
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const imageBuffer = Buffer.from(imageBase64, 'base64');
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const blob = new Blob([imageBuffer], { type: 'image/png' });
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formData.append('img', blob, 'image.png');
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formData.append('outtype', 'json');
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try {
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const response = await fetch(`${PADDLEOCR_URL}/ocr`, {
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method: 'POST',
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body: formData,
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});
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if (!response.ok) return '';
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const data = await response.json();
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if (data.success && data.results) {
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return data.results.map((r: { text: string }) => r.text).join('\n');
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}
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} catch {
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// PaddleOCR unavailable
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}
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return '';
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}
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/**
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* Build prompt with optional OCR text
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*/
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function buildPrompt(ocrText: string): string {
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const base = `You are an invoice parser. Extract the following fields from this invoice:
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1. invoice_number: The invoice/receipt number
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2. invoice_date: Date in YYYY-MM-DD format
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3. vendor_name: Company that issued the invoice
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4. currency: EUR, USD, etc.
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5. net_amount: Amount before tax (if shown)
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6. vat_amount: Tax/VAT amount (if shown, 0 if reverse charge or no tax)
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7. total_amount: Final amount due
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Return ONLY valid JSON in this exact format:
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{"invoice_number":"XXX","invoice_date":"YYYY-MM-DD","vendor_name":"Company Name","currency":"EUR","net_amount":100.00,"vat_amount":19.00,"total_amount":119.00}
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If a field is not visible, use null for strings or 0 for numbers.
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No explanation, just the JSON object.`;
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if (ocrText) {
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return `${base}
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OCR text extracted from the invoice:
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---
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${ocrText}
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---
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Cross-reference the image with the OCR text above for accuracy.`;
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}
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return base;
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}
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/**
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* Convert PDF to PNG images using ImageMagick
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*/
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function convertPdfToImages(pdfPath: string): string[] {
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const tempDir = fs.mkdtempSync(path.join(os.tmpdir(), 'pdf-convert-'));
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const outputPattern = path.join(tempDir, 'page-%d.png');
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try {
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execSync(
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`convert -density 200 -quality 90 "${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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* Single extraction pass
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*/
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async function extractOnce(images: string[], passNum: number, ocrText: string = ''): Promise<IInvoice> {
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const payload = {
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model: MODEL,
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prompt: buildPrompt(ocrText),
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images,
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stream: true,
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options: {
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num_predict: 2048,
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temperature: 0.1,
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},
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};
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const response = await fetch(`${OLLAMA_URL}/api/generate`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(payload),
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});
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if (!response.ok) {
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throw new Error(`Ollama API error: ${response.status}`);
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}
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const reader = response.body?.getReader();
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if (!reader) {
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throw new Error('No response body');
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}
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const decoder = new TextDecoder();
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let fullText = '';
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while (true) {
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const { done, value } = await reader.read();
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if (done) break;
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const chunk = decoder.decode(value, { stream: true });
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const lines = chunk.split('\n').filter((l) => l.trim());
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for (const line of lines) {
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try {
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const json = JSON.parse(line);
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if (json.response) {
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fullText += json.response;
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}
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} catch {
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// Skip invalid JSON lines
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}
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}
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}
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// Extract JSON from response
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const startIdx = fullText.indexOf('{');
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const endIdx = fullText.lastIndexOf('}') + 1;
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if (startIdx < 0 || endIdx <= startIdx) {
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throw new Error(`No JSON object found in response: ${fullText.substring(0, 200)}`);
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}
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const jsonStr = fullText.substring(startIdx, endIdx);
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return JSON.parse(jsonStr);
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}
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/**
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* Create a hash of invoice for comparison (using key fields)
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*/
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function hashInvoice(invoice: IInvoice): string {
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return `${invoice.invoice_number}|${invoice.invoice_date}|${invoice.total_amount.toFixed(2)}`;
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}
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/**
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* Extract with majority voting - run until 2 passes match
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*/
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async function extractWithConsensus(images: string[], invoiceName: string, maxPasses: number = 5): Promise<IInvoice> {
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const results: Array<{ invoice: IInvoice; hash: string }> = [];
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const hashCounts: Map<string, number> = new Map();
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// Extract OCR text from first page
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const ocrText = await extractOcrText(images[0]);
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if (ocrText) {
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console.log(` [OCR] Extracted ${ocrText.split('\n').length} text lines`);
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}
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for (let pass = 1; pass <= maxPasses; pass++) {
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try {
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const invoice = await extractOnce(images, pass, ocrText);
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const hash = hashInvoice(invoice);
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results.push({ invoice, hash });
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hashCounts.set(hash, (hashCounts.get(hash) || 0) + 1);
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console.log(` [Pass ${pass}] ${invoice.invoice_number} | ${invoice.invoice_date} | ${invoice.total_amount} ${invoice.currency}`);
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// Check if we have consensus (2+ matching)
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const count = hashCounts.get(hash)!;
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if (count >= 2) {
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console.log(` [Consensus] Reached after ${pass} passes`);
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return invoice;
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}
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} catch (err) {
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console.log(` [Pass ${pass}] Error: ${err}`);
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}
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}
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// No consensus reached - return the most common result
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let bestHash = '';
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let bestCount = 0;
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for (const [hash, count] of hashCounts) {
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if (count > bestCount) {
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bestCount = count;
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bestHash = hash;
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}
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}
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if (!bestHash) {
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throw new Error(`No valid results for ${invoiceName}`);
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}
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const best = results.find((r) => r.hash === bestHash)!;
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console.log(` [No consensus] Using most common result (${bestCount}/${maxPasses} passes)`);
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return best.invoice;
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}
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/**
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* Compare extracted invoice against expected
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*/
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function compareInvoice(
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extracted: IInvoice,
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expected: IInvoice
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): { match: boolean; errors: string[] } {
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const errors: string[] = [];
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// Compare invoice number (normalize by removing spaces and case)
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const extNum = extracted.invoice_number?.replace(/\s/g, '').toLowerCase() || '';
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const expNum = expected.invoice_number?.replace(/\s/g, '').toLowerCase() || '';
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if (extNum !== expNum) {
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errors.push(`invoice_number: expected "${expected.invoice_number}", got "${extracted.invoice_number}"`);
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}
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// Compare date
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if (extracted.invoice_date !== expected.invoice_date) {
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errors.push(`invoice_date: expected "${expected.invoice_date}", got "${extracted.invoice_date}"`);
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}
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// Compare total amount (with tolerance)
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if (Math.abs(extracted.total_amount - expected.total_amount) > 0.02) {
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errors.push(`total_amount: expected ${expected.total_amount}, got ${extracted.total_amount}`);
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}
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// Compare currency
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if (extracted.currency?.toUpperCase() !== expected.currency?.toUpperCase()) {
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errors.push(`currency: expected "${expected.currency}", got "${extracted.currency}"`);
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}
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return { match: errors.length === 0, errors };
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}
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/**
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* Find all test cases (PDF + JSON pairs) in .nogit/invoices/
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*/
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function findTestCases(): Array<{ name: string; pdfPath: string; jsonPath: string }> {
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const testDir = path.join(process.cwd(), '.nogit/invoices');
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if (!fs.existsSync(testDir)) {
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return [];
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}
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const files = fs.readdirSync(testDir);
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const pdfFiles = files.filter((f) => f.endsWith('.pdf'));
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const testCases: Array<{ name: string; pdfPath: string; jsonPath: string }> = [];
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for (const pdf of pdfFiles) {
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const baseName = pdf.replace('.pdf', '');
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const jsonFile = `${baseName}.json`;
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if (files.includes(jsonFile)) {
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testCases.push({
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name: baseName,
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pdfPath: path.join(testDir, pdf),
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jsonPath: path.join(testDir, jsonFile),
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});
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}
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}
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return testCases;
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}
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// Tests
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tap.test('should connect to Ollama API', async () => {
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const response = await fetch(`${OLLAMA_URL}/api/tags`);
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expect(response.ok).toBeTrue();
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const data = await response.json();
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expect(data.models).toBeArray();
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});
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tap.test('should have MiniCPM-V 4.5 model loaded', async () => {
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const response = await fetch(`${OLLAMA_URL}/api/tags`);
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const data = await response.json();
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const modelNames = data.models.map((m: { name: string }) => m.name);
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expect(modelNames.some((name: string) => name.includes('minicpm-v4.5'))).toBeTrue();
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});
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// Dynamic test for each PDF/JSON pair
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const testCases = findTestCases();
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console.log(`\nFound ${testCases.length} invoice test cases\n`);
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let passedCount = 0;
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let failedCount = 0;
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const processingTimes: number[] = [];
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for (const testCase of testCases) {
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tap.test(`should extract invoice: ${testCase.name}`, async () => {
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// Load expected data
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const expected: IInvoice = JSON.parse(fs.readFileSync(testCase.jsonPath, 'utf-8'));
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console.log(`\n=== ${testCase.name} ===`);
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console.log(`Expected: ${expected.invoice_number} | ${expected.invoice_date} | ${expected.total_amount} ${expected.currency}`);
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const startTime = Date.now();
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// Convert PDF to images
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const images = convertPdfToImages(testCase.pdfPath);
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console.log(` Pages: ${images.length}`);
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// Extract with consensus voting
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const extracted = await extractWithConsensus(images, testCase.name);
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const endTime = Date.now();
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const elapsedMs = endTime - startTime;
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processingTimes.push(elapsedMs);
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// Compare results
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const result = compareInvoice(extracted, expected);
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if (result.match) {
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passedCount++;
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console.log(` Result: MATCH (${(elapsedMs / 1000).toFixed(1)}s)`);
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} else {
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failedCount++;
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console.log(` Result: MISMATCH (${(elapsedMs / 1000).toFixed(1)}s)`);
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result.errors.forEach((e) => console.log(` - ${e}`));
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}
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// Assert match
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expect(result.match).toBeTrue();
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});
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}
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tap.test('summary', async () => {
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const totalInvoices = testCases.length;
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const accuracy = totalInvoices > 0 ? (passedCount / totalInvoices) * 100 : 0;
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const totalTimeMs = processingTimes.reduce((a, b) => a + b, 0);
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const avgTimeMs = processingTimes.length > 0 ? totalTimeMs / processingTimes.length : 0;
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const avgTimeSec = avgTimeMs / 1000;
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const totalTimeSec = totalTimeMs / 1000;
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console.log(`\n========================================`);
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console.log(` Invoice Extraction Summary`);
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console.log(`========================================`);
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console.log(` Passed: ${passedCount}/${totalInvoices}`);
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console.log(` Failed: ${failedCount}/${totalInvoices}`);
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console.log(` Accuracy: ${accuracy.toFixed(1)}%`);
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console.log(`----------------------------------------`);
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console.log(` Total time: ${totalTimeSec.toFixed(1)}s`);
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console.log(` Avg per inv: ${avgTimeSec.toFixed(1)}s`);
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console.log(`========================================\n`);
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});
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export default tap.start();
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@@ -7,7 +7,7 @@ import * as os from 'os';
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const OLLAMA_URL = 'http://localhost:11434';
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const MODEL = 'openbmb/minicpm-v4.5:q8_0';
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const BANK_STATEMENT_PROMPT = `You are a bank statement parser. Extract EVERY transaction from the table.
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const EXTRACT_PROMPT = `You are a bank statement parser. Extract EVERY transaction from the table.
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Read the Amount column carefully:
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- "- 21,47 €" means DEBIT, output as: -21.47
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@@ -16,7 +16,7 @@ Read the Amount column carefully:
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For each row output: {"date":"YYYY-MM-DD","counterparty":"NAME","amount":-21.47}
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Do not skip any rows. Return complete JSON array:`;
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Do not skip any rows. Return ONLY the JSON array, no explanation.`;
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interface ITransaction {
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date: string;
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@@ -53,12 +53,12 @@ function convertPdfToImages(pdfPath: string): string[] {
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}
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/**
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* Extract transactions from images using Ollama with streaming
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* Single extraction pass
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*/
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async function extractTransactionsStreaming(images: string[]): Promise<ITransaction[]> {
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async function extractOnce(images: string[], passNum: number): Promise<ITransaction[]> {
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const payload = {
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model: MODEL,
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prompt: BANK_STATEMENT_PROMPT,
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prompt: EXTRACT_PROMPT,
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images,
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stream: true,
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options: {
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@@ -86,7 +86,8 @@ async function extractTransactionsStreaming(images: string[]): Promise<ITransact
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let fullText = '';
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let lineBuffer = '';
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// Stream and print output (buffer until newline for cleaner display)
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console.log(`[Pass ${passNum}] Extracting...`);
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while (true) {
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const { done, value } = await reader.read();
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if (done) break;
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@@ -116,13 +117,11 @@ async function extractTransactionsStreaming(images: string[]): Promise<ITransact
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}
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}
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// Print any remaining buffer
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if (lineBuffer) {
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console.log(lineBuffer);
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}
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console.log('');
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// Parse JSON from response
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const startIdx = fullText.indexOf('[');
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const endIdx = fullText.lastIndexOf(']') + 1;
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@@ -133,6 +132,60 @@ async function extractTransactionsStreaming(images: string[]): Promise<ITransact
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return JSON.parse(fullText.substring(startIdx, endIdx));
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}
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/**
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* Create a hash of transactions for comparison
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*/
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function hashTransactions(transactions: ITransaction[]): string {
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return transactions
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.map((t) => `${t.date}|${t.amount.toFixed(2)}`)
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.sort()
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.join(';');
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}
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/**
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* Extract with majority voting - run until 2 passes match
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*/
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async function extractWithConsensus(images: string[], maxPasses: number = 5): Promise<ITransaction[]> {
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const results: Array<{ transactions: ITransaction[]; hash: string }> = [];
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const hashCounts: Map<string, number> = new Map();
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for (let pass = 1; pass <= maxPasses; pass++) {
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const transactions = await extractOnce(images, pass);
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const hash = hashTransactions(transactions);
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results.push({ transactions, hash });
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hashCounts.set(hash, (hashCounts.get(hash) || 0) + 1);
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console.log(`[Pass ${pass}] Got ${transactions.length} transactions (hash: ${hash.substring(0, 20)}...)`);
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// Check if we have consensus (2+ matching)
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const count = hashCounts.get(hash)!;
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if (count >= 2) {
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console.log(`[Consensus] Reached after ${pass} passes (${count} matching results)`);
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return transactions;
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}
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// After 2 passes, if no match yet, continue
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if (pass >= 2) {
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console.log(`[Pass ${pass}] No consensus yet, trying again...`);
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}
|
||||
}
|
||||
|
||||
// No consensus reached - return the most common result
|
||||
let bestHash = '';
|
||||
let bestCount = 0;
|
||||
for (const [hash, count] of hashCounts) {
|
||||
if (count > bestCount) {
|
||||
bestCount = count;
|
||||
bestHash = hash;
|
||||
}
|
||||
}
|
||||
|
||||
const best = results.find((r) => r.hash === bestHash)!;
|
||||
console.log(`[No consensus] Using most common result (${bestCount}/${maxPasses} passes)`);
|
||||
return best.transactions;
|
||||
}
|
||||
|
||||
/**
|
||||
* Compare extracted transactions against expected
|
||||
*/
|
||||
@@ -227,16 +280,15 @@ for (const testCase of testCases) {
|
||||
// Convert PDF to images
|
||||
console.log('Converting PDF to images...');
|
||||
const images = convertPdfToImages(testCase.pdfPath);
|
||||
console.log(`Converted: ${images.length} pages`);
|
||||
console.log(`Converted: ${images.length} pages\n`);
|
||||
|
||||
// Extract transactions with streaming output
|
||||
console.log('Extracting transactions (streaming)...\n');
|
||||
const extracted = await extractTransactionsStreaming(images);
|
||||
console.log(`Extracted: ${extracted.length} transactions`);
|
||||
// Extract with consensus voting
|
||||
const extracted = await extractWithConsensus(images);
|
||||
console.log(`\nFinal: ${extracted.length} transactions`);
|
||||
|
||||
// Compare results
|
||||
const result = compareTransactions(extracted, expected);
|
||||
console.log(`Matches: ${result.matches}/${result.total}`);
|
||||
console.log(`Accuracy: ${result.matches}/${result.total}`);
|
||||
|
||||
if (result.errors.length > 0) {
|
||||
console.log('Errors:');
|
||||
|
||||
Reference in New Issue
Block a user