feat(tests): add Ministral 3 vision tests and improve invoice extraction pipeline to use Ollama chat schema, sanitization, and multi-page support
This commit is contained in:
@@ -358,3 +358,16 @@ export async function ensureQwen25(): Promise<boolean> {
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// Then ensure the Qwen2.5 model is pulled
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return ensureOllamaModel('qwen2.5:7b');
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}
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/**
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* Ensure Ministral 3 8B model is available (for structured JSON extraction)
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* Ministral 3 has native JSON output support and OCR-style document extraction
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*/
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export async function ensureMinistral3(): Promise<boolean> {
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// First ensure the Ollama service (MiniCPM container) is running
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const ollamaOk = await ensureMiniCpm();
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if (!ollamaOk) return false;
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// Then ensure the Ministral 3 8B model is pulled
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return ensureOllamaModel('ministral-3:8b');
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}
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348
test/test.bankstatements.ministral3.ts
Normal file
348
test/test.bankstatements.ministral3.ts
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@@ -0,0 +1,348 @@
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/**
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* Bank Statement extraction using Ministral 3 Vision (Direct)
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*
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* NO OCR pipeline needed - Ministral 3 has built-in vision encoder:
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* 1. Convert PDF to images
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* 2. Send images directly to Ministral 3 via Ollama
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* 3. Extract transactions as structured JSON
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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 { ensureMinistral3 } from './helpers/docker.js';
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const OLLAMA_URL = 'http://localhost:11434';
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const VISION_MODEL = 'ministral-3:8b';
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interface ITransaction {
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date: string;
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counterparty: string;
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amount: number;
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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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* Extract transactions from a single page image using Ministral 3 Vision
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*/
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async function extractTransactionsFromPage(image: string, pageNum: number): Promise<ITransaction[]> {
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console.log(` [Vision] Processing page ${pageNum}`);
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// JSON schema for array of transactions
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const transactionSchema = {
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type: 'array',
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items: {
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type: 'object',
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properties: {
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date: { type: 'string', description: 'Transaction date in YYYY-MM-DD format' },
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counterparty: { type: 'string', description: 'Name of the other party' },
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amount: { type: 'number', description: 'Amount (negative for debits, positive for credits)' },
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},
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required: ['date', 'counterparty', 'amount'],
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},
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};
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const prompt = `Extract ALL bank transactions from this bank statement page.
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For each transaction, extract:
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- date: Transaction date in YYYY-MM-DD format
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- counterparty: The name/description of the other party (merchant, payee, etc.)
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- amount: The amount as a number (NEGATIVE for debits/expenses, POSITIVE for credits/income)
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Return a JSON array of transactions. If no transactions visible, return empty array [].
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Example: [{"date":"2021-06-01","counterparty":"AMAZON","amount":-50.00}]`;
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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: VISION_MODEL,
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messages: [
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{
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role: 'user',
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content: prompt,
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images: [image],
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},
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],
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format: transactionSchema,
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stream: true,
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options: {
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num_predict: 4096, // Bank statements can have many transactions
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temperature: 0.0,
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},
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}),
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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.message?.content) {
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fullText += json.message.content;
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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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// Parse JSON response
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let jsonStr = fullText.trim();
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if (jsonStr.startsWith('```json')) jsonStr = jsonStr.slice(7);
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else if (jsonStr.startsWith('```')) jsonStr = jsonStr.slice(3);
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if (jsonStr.endsWith('```')) jsonStr = jsonStr.slice(0, -3);
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jsonStr = jsonStr.trim();
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// Find array boundaries
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const startIdx = jsonStr.indexOf('[');
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const endIdx = jsonStr.lastIndexOf(']') + 1;
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if (startIdx < 0 || endIdx <= startIdx) {
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console.log(` [Page ${pageNum}] No transactions found`);
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return [];
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}
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try {
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const parsed = JSON.parse(jsonStr.substring(startIdx, endIdx));
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console.log(` [Page ${pageNum}] Found ${parsed.length} transactions`);
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return parsed.map((t: { date?: string; counterparty?: string; amount?: number }) => ({
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date: t.date || '',
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counterparty: t.counterparty || '',
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amount: parseFloat(String(t.amount)) || 0,
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}));
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} catch (e) {
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console.log(` [Page ${pageNum}] Parse error: ${e}`);
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return [];
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}
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}
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/**
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* Extract all transactions from all pages
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*/
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async function extractAllTransactions(images: string[]): Promise<ITransaction[]> {
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const allTransactions: ITransaction[] = [];
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for (let i = 0; i < images.length; i++) {
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const pageTransactions = await extractTransactionsFromPage(images[i], i + 1);
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allTransactions.push(...pageTransactions);
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}
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return allTransactions;
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}
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/**
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* Normalize date to YYYY-MM-DD
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*/
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function normalizeDate(dateStr: string): string {
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if (!dateStr) return '';
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if (/^\d{4}-\d{2}-\d{2}$/.test(dateStr)) return dateStr;
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// Handle DD/MM/YYYY or DD.MM.YYYY
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const match = dateStr.match(/^(\d{1,2})[\/.](\d{1,2})[\/.](\d{4})$/);
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if (match) {
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return `${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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}
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/**
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* Compare extracted transactions vs expected
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*/
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function compareTransactions(
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extracted: ITransaction[],
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expected: ITransaction[]
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): { matchRate: number; matched: number; missed: number; extra: number; errors: string[] } {
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const errors: string[] = [];
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let matched = 0;
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// Normalize all dates
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const normalizedExtracted = extracted.map((t) => ({
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...t,
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date: normalizeDate(t.date),
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counterparty: t.counterparty.toUpperCase().trim(),
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}));
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const normalizedExpected = expected.map((t) => ({
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...t,
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date: normalizeDate(t.date),
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counterparty: t.counterparty.toUpperCase().trim(),
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}));
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// Try to match each expected transaction
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const matchedIndices = new Set<number>();
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for (const exp of normalizedExpected) {
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let found = false;
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for (let i = 0; i < normalizedExtracted.length; i++) {
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if (matchedIndices.has(i)) continue;
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const ext = normalizedExtracted[i];
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// Match by date + amount (counterparty names can vary)
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if (ext.date === exp.date && Math.abs(ext.amount - exp.amount) < 0.02) {
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matched++;
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matchedIndices.add(i);
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found = true;
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break;
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}
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}
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if (!found) {
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errors.push(`Missing: ${exp.date} | ${exp.counterparty} | ${exp.amount}`);
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}
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}
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const missed = expected.length - matched;
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const extra = extracted.length - matched;
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const matchRate = expected.length > 0 ? (matched / expected.length) * 100 : 0;
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return { matchRate, matched, missed, extra, errors };
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}
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/**
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* Find test cases (PDF + JSON pairs in .nogit/)
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*/
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function findTestCases(): Array<{ name: string; pdfPath: string; jsonPath: string }> {
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const testDir = path.join(process.cwd(), '.nogit');
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if (!fs.existsSync(testDir)) return [];
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const files = fs.readdirSync(testDir);
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const testCases: Array<{ name: string; pdfPath: string; jsonPath: string }> = [];
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for (const pdf of files.filter((f) => f.endsWith('.pdf'))) {
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const baseName = pdf.replace('.pdf', '');
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const jsonFile = `${baseName}.json`;
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if (files.includes(jsonFile)) {
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// Skip invoice files - only bank statements
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if (!baseName.includes('invoice')) {
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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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}
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return testCases.sort((a, b) => a.name.localeCompare(b.name));
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}
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// Tests
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tap.test('setup: ensure Ministral 3 is running', async () => {
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console.log('\n[Setup] Checking Ministral 3...\n');
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const ok = await ensureMinistral3();
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expect(ok).toBeTrue();
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console.log('\n[Setup] Ready!\n');
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});
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const testCases = findTestCases();
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console.log(`\nFound ${testCases.length} bank statement test cases (Ministral 3 Vision)\n`);
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let totalMatched = 0;
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let totalExpected = 0;
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const times: number[] = [];
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for (const testCase of testCases) {
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tap.test(`should extract bank statement: ${testCase.name}`, async () => {
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const expected: ITransaction[] = 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.length} transactions`);
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const start = Date.now();
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const images = convertPdfToImages(testCase.pdfPath);
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console.log(` Pages: ${images.length}`);
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const extracted = await extractAllTransactions(images);
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const elapsed = Date.now() - start;
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times.push(elapsed);
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console.log(` Extracted: ${extracted.length} transactions`);
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const result = compareTransactions(extracted, expected);
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totalMatched += result.matched;
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totalExpected += expected.length;
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console.log(` Match rate: ${result.matchRate.toFixed(1)}% (${result.matched}/${expected.length})`);
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console.log(` Missed: ${result.missed}, Extra: ${result.extra}`);
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console.log(` Time: ${(elapsed / 1000).toFixed(1)}s`);
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if (result.errors.length > 0 && result.errors.length <= 5) {
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result.errors.forEach((e) => console.log(` - ${e}`));
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} else if (result.errors.length > 5) {
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console.log(` (${result.errors.length} missing transactions)`);
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}
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// Consider it a pass if we match at least 70% of transactions
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expect(result.matchRate).toBeGreaterThan(70);
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});
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}
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tap.test('summary', async () => {
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const overallMatchRate = totalExpected > 0 ? (totalMatched / totalExpected) * 100 : 0;
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const totalTime = times.reduce((a, b) => a + b, 0) / 1000;
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const avgTime = times.length > 0 ? totalTime / times.length : 0;
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console.log(`\n======================================================`);
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console.log(` Bank Statement Extraction Summary (Ministral 3)`);
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console.log(`======================================================`);
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console.log(` Method: Ministral 3 8B Vision (Direct)`);
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console.log(` Statements: ${testCases.length}`);
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console.log(` Matched: ${totalMatched}/${totalExpected} transactions`);
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console.log(` Match rate: ${overallMatchRate.toFixed(1)}%`);
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console.log(`------------------------------------------------------`);
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console.log(` Total time: ${totalTime.toFixed(1)}s`);
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console.log(` Avg per stmt: ${avgTime.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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355
test/test.invoices.ministral3.ts
Normal file
355
test/test.invoices.ministral3.ts
Normal file
@@ -0,0 +1,355 @@
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/**
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* Invoice extraction using Ministral 3 Vision (Direct)
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*
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* NO PaddleOCR needed - Ministral 3 has built-in vision encoder:
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* 1. Convert PDF to images
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* 2. Send images directly to Ministral 3 via Ollama
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* 3. Extract structured JSON with native schema support
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*
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* This is the simplest possible pipeline.
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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 { ensureMinistral3 } from './helpers/docker.js';
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const OLLAMA_URL = 'http://localhost:11434';
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const VISION_MODEL = 'ministral-3:8b';
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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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/**
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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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* Extract invoice data directly from images using Ministral 3 Vision
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*/
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async function extractInvoiceFromImages(images: string[]): Promise<IInvoice> {
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console.log(` [Vision] Processing ${images.length} page(s) with Ministral 3`);
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// JSON schema for structured output
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const invoiceSchema = {
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type: 'object',
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properties: {
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invoice_number: { type: 'string' },
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invoice_date: { type: 'string' },
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vendor_name: { type: 'string' },
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currency: { type: 'string' },
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net_amount: { type: 'number' },
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vat_amount: { type: 'number' },
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total_amount: { type: 'number' },
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},
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required: ['invoice_number', 'invoice_date', 'vendor_name', 'currency', 'net_amount', 'vat_amount', 'total_amount'],
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};
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const prompt = `Extract invoice data from this document image(s).
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Find and return:
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- invoice_number: The invoice number/ID (look for "Invoice No", "Invoice #", "Rechnung Nr")
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- invoice_date: The invoice date in YYYY-MM-DD format
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- vendor_name: The company issuing the invoice (in letterhead)
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- currency: EUR, USD, or GBP
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- total_amount: The FINAL total amount due
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- net_amount: Amount before VAT/tax
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- vat_amount: VAT/tax amount
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Return ONLY valid JSON.`;
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const response = await fetch(`${OLLAMA_URL}/api/chat`, {
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method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({
|
||||
model: VISION_MODEL,
|
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messages: [
|
||||
{
|
||||
role: 'user',
|
||||
content: prompt,
|
||||
images: images, // Send all page images
|
||||
},
|
||||
],
|
||||
format: invoiceSchema,
|
||||
stream: true,
|
||||
options: {
|
||||
num_predict: 512,
|
||||
temperature: 0.0,
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`Ollama API error: ${response.status}`);
|
||||
}
|
||||
|
||||
const reader = response.body?.getReader();
|
||||
if (!reader) {
|
||||
throw new Error('No response body');
|
||||
}
|
||||
|
||||
const decoder = new TextDecoder();
|
||||
let fullText = '';
|
||||
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
|
||||
const chunk = decoder.decode(value, { stream: true });
|
||||
const lines = chunk.split('\n').filter((l) => l.trim());
|
||||
|
||||
for (const line of lines) {
|
||||
try {
|
||||
const json = JSON.parse(line);
|
||||
if (json.message?.content) {
|
||||
fullText += json.message.content;
|
||||
}
|
||||
} catch {
|
||||
// Skip invalid JSON lines
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Parse JSON response
|
||||
let jsonStr = fullText.trim();
|
||||
|
||||
if (jsonStr.startsWith('```json')) jsonStr = jsonStr.slice(7);
|
||||
else if (jsonStr.startsWith('```')) jsonStr = jsonStr.slice(3);
|
||||
if (jsonStr.endsWith('```')) jsonStr = jsonStr.slice(0, -3);
|
||||
jsonStr = jsonStr.trim();
|
||||
|
||||
const startIdx = jsonStr.indexOf('{');
|
||||
const endIdx = jsonStr.lastIndexOf('}') + 1;
|
||||
|
||||
if (startIdx < 0 || endIdx <= startIdx) {
|
||||
throw new Error(`No JSON found: ${fullText.substring(0, 200)}`);
|
||||
}
|
||||
|
||||
const parsed = JSON.parse(jsonStr.substring(startIdx, endIdx));
|
||||
|
||||
return {
|
||||
invoice_number: parsed.invoice_number || null,
|
||||
invoice_date: parsed.invoice_date || null,
|
||||
vendor_name: parsed.vendor_name || null,
|
||||
currency: parsed.currency || 'EUR',
|
||||
net_amount: parseFloat(parsed.net_amount) || 0,
|
||||
vat_amount: parseFloat(parsed.vat_amount) || 0,
|
||||
total_amount: parseFloat(parsed.total_amount) || 0,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract with consensus voting (2 agreeing passes)
|
||||
*/
|
||||
async function extractWithConsensus(images: string[], name: string, maxPasses: number = 3): Promise<IInvoice> {
|
||||
const results: Array<{ invoice: IInvoice; hash: string }> = [];
|
||||
const hashCounts: Map<string, number> = new Map();
|
||||
|
||||
for (let pass = 1; pass <= maxPasses; pass++) {
|
||||
try {
|
||||
const invoice = await extractInvoiceFromImages(images);
|
||||
const hash = `${invoice.invoice_number}|${invoice.invoice_date}|${invoice.total_amount?.toFixed(2)}`;
|
||||
results.push({ invoice, hash });
|
||||
hashCounts.set(hash, (hashCounts.get(hash) || 0) + 1);
|
||||
|
||||
console.log(` [Pass ${pass}] ${invoice.invoice_number} | ${invoice.invoice_date} | ${invoice.total_amount} ${invoice.currency}`);
|
||||
|
||||
if (hashCounts.get(hash)! >= 2) {
|
||||
console.log(` [Consensus] Reached after ${pass} passes`);
|
||||
return invoice;
|
||||
}
|
||||
} catch (err) {
|
||||
console.log(` [Pass ${pass}] Error: ${err}`);
|
||||
}
|
||||
}
|
||||
|
||||
// Return most common result
|
||||
let bestHash = '';
|
||||
let bestCount = 0;
|
||||
for (const [hash, count] of hashCounts) {
|
||||
if (count > bestCount) {
|
||||
bestCount = count;
|
||||
bestHash = hash;
|
||||
}
|
||||
}
|
||||
|
||||
if (!bestHash) throw new Error(`No valid results for ${name}`);
|
||||
|
||||
console.log(` [No consensus] Using best result (${bestCount}/${maxPasses})`);
|
||||
return results.find((r) => r.hash === bestHash)!.invoice;
|
||||
}
|
||||
|
||||
/**
|
||||
* Normalize date to YYYY-MM-DD
|
||||
*/
|
||||
function normalizeDate(dateStr: string | null): string {
|
||||
if (!dateStr) return '';
|
||||
if (/^\d{4}-\d{2}-\d{2}$/.test(dateStr)) return dateStr;
|
||||
|
||||
const monthMap: Record<string, string> = {
|
||||
JAN: '01', FEB: '02', MAR: '03', APR: '04', MAY: '05', JUN: '06',
|
||||
JUL: '07', AUG: '08', SEP: '09', OCT: '10', NOV: '11', DEC: '12',
|
||||
};
|
||||
|
||||
let match = dateStr.match(/^(\d{1,2})-([A-Z]{3})-(\d{4})$/i);
|
||||
if (match) {
|
||||
return `${match[3]}-${monthMap[match[2].toUpperCase()] || '01'}-${match[1].padStart(2, '0')}`;
|
||||
}
|
||||
|
||||
match = dateStr.match(/^(\d{1,2})[\/.](\d{1,2})[\/.](\d{4})$/);
|
||||
if (match) {
|
||||
return `${match[3]}-${match[2].padStart(2, '0')}-${match[1].padStart(2, '0')}`;
|
||||
}
|
||||
|
||||
return dateStr;
|
||||
}
|
||||
|
||||
/**
|
||||
* Compare extracted vs expected
|
||||
*/
|
||||
function compareInvoice(extracted: IInvoice, expected: IInvoice): { match: boolean; errors: string[] } {
|
||||
const errors: string[] = [];
|
||||
|
||||
const extNum = extracted.invoice_number?.replace(/\s/g, '').toLowerCase() || '';
|
||||
const expNum = expected.invoice_number?.replace(/\s/g, '').toLowerCase() || '';
|
||||
if (extNum !== expNum) {
|
||||
errors.push(`invoice_number: expected "${expected.invoice_number}", got "${extracted.invoice_number}"`);
|
||||
}
|
||||
|
||||
if (normalizeDate(extracted.invoice_date) !== normalizeDate(expected.invoice_date)) {
|
||||
errors.push(`invoice_date: expected "${expected.invoice_date}", got "${extracted.invoice_date}"`);
|
||||
}
|
||||
|
||||
if (Math.abs(extracted.total_amount - expected.total_amount) > 0.02) {
|
||||
errors.push(`total_amount: expected ${expected.total_amount}, got ${extracted.total_amount}`);
|
||||
}
|
||||
|
||||
if (extracted.currency?.toUpperCase() !== expected.currency?.toUpperCase()) {
|
||||
errors.push(`currency: expected "${expected.currency}", got "${extracted.currency}"`);
|
||||
}
|
||||
|
||||
return { match: errors.length === 0, errors };
|
||||
}
|
||||
|
||||
/**
|
||||
* Find test cases
|
||||
*/
|
||||
function findTestCases(): Array<{ name: string; pdfPath: string; jsonPath: string }> {
|
||||
const testDir = path.join(process.cwd(), '.nogit/invoices');
|
||||
if (!fs.existsSync(testDir)) return [];
|
||||
|
||||
const files = fs.readdirSync(testDir);
|
||||
const testCases: Array<{ name: string; pdfPath: string; jsonPath: string }> = [];
|
||||
|
||||
for (const pdf of files.filter((f) => f.endsWith('.pdf'))) {
|
||||
const baseName = pdf.replace('.pdf', '');
|
||||
const jsonFile = `${baseName}.json`;
|
||||
if (files.includes(jsonFile)) {
|
||||
testCases.push({
|
||||
name: baseName,
|
||||
pdfPath: path.join(testDir, pdf),
|
||||
jsonPath: path.join(testDir, jsonFile),
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
return testCases.sort((a, b) => a.name.localeCompare(b.name));
|
||||
}
|
||||
|
||||
// Tests
|
||||
|
||||
tap.test('setup: ensure Ministral 3 is running', async () => {
|
||||
console.log('\n[Setup] Checking Ministral 3...\n');
|
||||
const ok = await ensureMinistral3();
|
||||
expect(ok).toBeTrue();
|
||||
console.log('\n[Setup] Ready!\n');
|
||||
});
|
||||
|
||||
const testCases = findTestCases();
|
||||
console.log(`\nFound ${testCases.length} invoice test cases (Ministral 3 Vision Direct)\n`);
|
||||
|
||||
let passedCount = 0;
|
||||
let failedCount = 0;
|
||||
const times: 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 start = Date.now();
|
||||
const images = convertPdfToImages(testCase.pdfPath);
|
||||
console.log(` Pages: ${images.length}`);
|
||||
|
||||
const extracted = await extractWithConsensus(images, testCase.name);
|
||||
const elapsed = Date.now() - start;
|
||||
times.push(elapsed);
|
||||
|
||||
const result = compareInvoice(extracted, expected);
|
||||
|
||||
if (result.match) {
|
||||
passedCount++;
|
||||
console.log(` Result: MATCH (${(elapsed / 1000).toFixed(1)}s)`);
|
||||
} else {
|
||||
failedCount++;
|
||||
console.log(` Result: MISMATCH (${(elapsed / 1000).toFixed(1)}s)`);
|
||||
result.errors.forEach((e) => console.log(` - ${e}`));
|
||||
}
|
||||
|
||||
expect(result.match).toBeTrue();
|
||||
});
|
||||
}
|
||||
|
||||
tap.test('summary', async () => {
|
||||
const total = testCases.length;
|
||||
const accuracy = total > 0 ? (passedCount / total) * 100 : 0;
|
||||
const totalTime = times.reduce((a, b) => a + b, 0) / 1000;
|
||||
const avgTime = times.length > 0 ? totalTime / times.length : 0;
|
||||
|
||||
console.log(`\n======================================================`);
|
||||
console.log(` Invoice Extraction Summary (Ministral 3 Vision)`);
|
||||
console.log(`======================================================`);
|
||||
console.log(` Method: Ministral 3 8B Vision (Direct)`);
|
||||
console.log(` Passed: ${passedCount}/${total}`);
|
||||
console.log(` Failed: ${failedCount}/${total}`);
|
||||
console.log(` Accuracy: ${accuracy.toFixed(1)}%`);
|
||||
console.log(`------------------------------------------------------`);
|
||||
console.log(` Total time: ${totalTime.toFixed(1)}s`);
|
||||
console.log(` Avg per inv: ${avgTime.toFixed(1)}s`);
|
||||
console.log(`======================================================\n`);
|
||||
});
|
||||
|
||||
export default tap.start();
|
||||
@@ -90,61 +90,71 @@ async function parseDocument(imageBase64: string): Promise<string> {
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract invoice fields from structured HTML using Qwen2.5 (text-only model)
|
||||
* Sanitize HTML to remove OCR artifacts that confuse the LLM
|
||||
* Minimal cleaning - only remove truly problematic patterns
|
||||
*/
|
||||
function sanitizeHtml(html: string): string {
|
||||
// Remove excessively repeated characters (OCR glitches)
|
||||
let sanitized = html.replace(/(\d)\1{20,}/g, '$1...');
|
||||
// Remove extremely long strings (corrupted data)
|
||||
sanitized = sanitized.replace(/\b[A-Za-z0-9]{50,}\b/g, '[OCR_ARTIFACT]');
|
||||
return sanitized;
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract invoice fields using simple direct prompt
|
||||
* The OCR output has clearly labeled fields - just ask the LLM to read them
|
||||
*/
|
||||
async function extractInvoiceFromHtml(html: string): Promise<IInvoice> {
|
||||
// Truncate if too long (HTML is more valuable per byte, allow more)
|
||||
const truncated = html.length > 16000 ? html.slice(0, 16000) : html;
|
||||
console.log(` [Extract] Processing ${truncated.length} chars of HTML`);
|
||||
const sanitized = sanitizeHtml(html);
|
||||
const truncated = sanitized.length > 32000 ? sanitized.slice(0, 32000) : sanitized;
|
||||
console.log(` [Extract] ${truncated.length} chars of HTML`);
|
||||
|
||||
const prompt = `You are an invoice data extractor. Extract the following fields from this HTML document (OCR output with semantic structure) and return ONLY a valid JSON object.
|
||||
|
||||
The HTML uses semantic tags:
|
||||
- <table> with <thead>/<tbody> for structured tables (invoice line items, totals)
|
||||
- <header> for document header (company info, invoice number)
|
||||
- <footer> for document footer (payment terms, legal text)
|
||||
- <section class="table-region"> for table regions
|
||||
- data-type and data-y attributes indicate block type and vertical position
|
||||
|
||||
Required fields:
|
||||
- invoice_number: The invoice/receipt/document number
|
||||
- invoice_date: Date in YYYY-MM-DD format (convert from any format)
|
||||
- vendor_name: Company that issued the invoice
|
||||
- currency: EUR, USD, GBP, etc.
|
||||
- net_amount: Amount before tax (number)
|
||||
- vat_amount: Tax/VAT amount (number, use 0 if reverse charge or not shown)
|
||||
- total_amount: Final total amount (number)
|
||||
|
||||
Example output format:
|
||||
{"invoice_number":"INV-123","invoice_date":"2022-01-28","vendor_name":"Adobe","currency":"EUR","net_amount":24.99,"vat_amount":0,"total_amount":24.99}
|
||||
|
||||
Rules:
|
||||
- Return ONLY the JSON object, no explanation or markdown
|
||||
- Use null for missing string fields
|
||||
- Use 0 for missing numeric fields
|
||||
- Convert dates to YYYY-MM-DD format (e.g., "28-JAN-2022" becomes "2022-01-28")
|
||||
- Extract numbers without currency symbols
|
||||
- Look for totals in <table> sections, especially rows with "Total", "Amount Due", "Grand Total"
|
||||
|
||||
HTML Document:
|
||||
${truncated}
|
||||
|
||||
JSON:`;
|
||||
|
||||
const payload = {
|
||||
model: TEXT_MODEL,
|
||||
prompt,
|
||||
stream: true,
|
||||
options: {
|
||||
num_predict: 512,
|
||||
temperature: 0.1,
|
||||
// JSON schema for structured output
|
||||
const invoiceSchema = {
|
||||
type: 'object',
|
||||
properties: {
|
||||
invoice_number: { type: 'string' },
|
||||
invoice_date: { type: 'string' },
|
||||
vendor_name: { type: 'string' },
|
||||
currency: { type: 'string' },
|
||||
net_amount: { type: 'number' },
|
||||
vat_amount: { type: 'number' },
|
||||
total_amount: { type: 'number' },
|
||||
},
|
||||
required: ['invoice_number', 'invoice_date', 'vendor_name', 'currency', 'net_amount', 'vat_amount', 'total_amount'],
|
||||
};
|
||||
|
||||
const response = await fetch(`${OLLAMA_URL}/api/generate`, {
|
||||
// Simple, direct prompt - the OCR output already has labeled fields
|
||||
const systemPrompt = `You read invoice HTML and extract labeled fields. Return JSON only.`;
|
||||
|
||||
const userPrompt = `Extract from this invoice HTML:
|
||||
- invoice_number: Find "Invoice no.", "Invoice #", "Invoice", "Rechnung", "Document No" and extract the value
|
||||
- invoice_date: Find "Invoice date", "Date", "Datum" and convert to YYYY-MM-DD format
|
||||
- vendor_name: The company name issuing the invoice (in header/letterhead)
|
||||
- currency: EUR, USD, or GBP (look for € $ £ symbols or text)
|
||||
- total_amount: Find "Total", "Grand Total", "Amount Due", "Gesamtbetrag" - the FINAL total amount
|
||||
- net_amount: Amount before VAT/tax (Subtotal, Net)
|
||||
- vat_amount: VAT/tax amount
|
||||
|
||||
HTML:
|
||||
${truncated}
|
||||
|
||||
Return ONLY valid JSON: {"invoice_number":"...", "invoice_date":"YYYY-MM-DD", "vendor_name":"...", "currency":"EUR", "net_amount":0, "vat_amount":0, "total_amount":0}`;
|
||||
|
||||
const response = await fetch(`${OLLAMA_URL}/api/chat`, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify(payload),
|
||||
body: JSON.stringify({
|
||||
model: TEXT_MODEL,
|
||||
messages: [
|
||||
{ role: 'system', content: systemPrompt },
|
||||
{ role: 'user', content: userPrompt },
|
||||
],
|
||||
format: invoiceSchema,
|
||||
stream: true,
|
||||
options: { num_predict: 512, temperature: 0.0 },
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
@@ -169,7 +179,9 @@ JSON:`;
|
||||
for (const line of lines) {
|
||||
try {
|
||||
const json = JSON.parse(line);
|
||||
if (json.response) {
|
||||
if (json.message?.content) {
|
||||
fullText += json.message.content;
|
||||
} else if (json.response) {
|
||||
fullText += json.response;
|
||||
}
|
||||
} catch {
|
||||
@@ -179,17 +191,37 @@ JSON:`;
|
||||
}
|
||||
|
||||
// Extract JSON from response
|
||||
const startIdx = fullText.indexOf('{');
|
||||
const endIdx = fullText.lastIndexOf('}') + 1;
|
||||
let jsonStr = fullText.trim();
|
||||
|
||||
// Remove markdown code block if present
|
||||
if (jsonStr.startsWith('```json')) {
|
||||
jsonStr = jsonStr.slice(7);
|
||||
} else if (jsonStr.startsWith('```')) {
|
||||
jsonStr = jsonStr.slice(3);
|
||||
}
|
||||
if (jsonStr.endsWith('```')) {
|
||||
jsonStr = jsonStr.slice(0, -3);
|
||||
}
|
||||
jsonStr = jsonStr.trim();
|
||||
|
||||
// Find JSON object boundaries
|
||||
const startIdx = jsonStr.indexOf('{');
|
||||
const endIdx = jsonStr.lastIndexOf('}') + 1;
|
||||
|
||||
if (startIdx < 0 || endIdx <= startIdx) {
|
||||
throw new Error(`No JSON object found in response: ${fullText.substring(0, 200)}`);
|
||||
}
|
||||
|
||||
const jsonStr = fullText.substring(startIdx, endIdx);
|
||||
const parsed = JSON.parse(jsonStr);
|
||||
jsonStr = jsonStr.substring(startIdx, endIdx);
|
||||
|
||||
// Ensure numeric fields are actually numbers
|
||||
let parsed;
|
||||
try {
|
||||
parsed = JSON.parse(jsonStr);
|
||||
} catch (e) {
|
||||
throw new Error(`Invalid JSON: ${jsonStr.substring(0, 200)}`);
|
||||
}
|
||||
|
||||
// Normalize response to expected format
|
||||
return {
|
||||
invoice_number: parsed.invoice_number || null,
|
||||
invoice_date: parsed.invoice_date || null,
|
||||
@@ -203,14 +235,23 @@ JSON:`;
|
||||
|
||||
/**
|
||||
* Single extraction pass: Parse with PaddleOCR-VL Full, extract with Qwen2.5 (text-only)
|
||||
* Processes ALL pages and concatenates HTML for multi-page invoice support
|
||||
*/
|
||||
async function extractOnce(images: string[], passNum: number): Promise<IInvoice> {
|
||||
// Parse document with full pipeline (PaddleOCR-VL) -> returns HTML
|
||||
const html = await parseDocument(images[0]);
|
||||
console.log(` [Parse] Got ${html.split('\n').length} lines of HTML`);
|
||||
// Parse ALL pages and concatenate HTML with page markers
|
||||
const htmlParts: string[] = [];
|
||||
|
||||
for (let i = 0; i < images.length; i++) {
|
||||
const pageHtml = await parseDocument(images[i]);
|
||||
// Add page marker for context
|
||||
htmlParts.push(`<!-- Page ${i + 1} -->\n${pageHtml}`);
|
||||
}
|
||||
|
||||
const fullHtml = htmlParts.join('\n\n');
|
||||
console.log(` [Parse] Got ${fullHtml.split('\n').length} lines from ${images.length} page(s)`);
|
||||
|
||||
// Extract invoice fields from HTML using text-only model (no images)
|
||||
return extractInvoiceFromHtml(html);
|
||||
return extractInvoiceFromHtml(fullHtml);
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
Reference in New Issue
Block a user