feat(tests): add Ministral 3 vision tests and improve invoice extraction pipeline to use Ollama chat schema, sanitization, and multi-page support
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@@ -90,61 +90,71 @@ async function parseDocument(imageBase64: string): Promise<string> {
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}
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/**
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* Extract invoice fields from structured HTML using Qwen2.5 (text-only model)
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* Sanitize HTML to remove OCR artifacts that confuse the LLM
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* Minimal cleaning - only remove truly problematic patterns
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*/
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function sanitizeHtml(html: string): string {
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// Remove excessively repeated characters (OCR glitches)
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let sanitized = html.replace(/(\d)\1{20,}/g, '$1...');
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// Remove extremely long strings (corrupted data)
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sanitized = sanitized.replace(/\b[A-Za-z0-9]{50,}\b/g, '[OCR_ARTIFACT]');
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return sanitized;
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}
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/**
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* Extract invoice fields using simple direct prompt
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* The OCR output has clearly labeled fields - just ask the LLM to read them
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*/
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async function extractInvoiceFromHtml(html: string): Promise<IInvoice> {
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// Truncate if too long (HTML is more valuable per byte, allow more)
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const truncated = html.length > 16000 ? html.slice(0, 16000) : html;
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console.log(` [Extract] Processing ${truncated.length} chars of HTML`);
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const sanitized = sanitizeHtml(html);
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const truncated = sanitized.length > 32000 ? sanitized.slice(0, 32000) : sanitized;
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console.log(` [Extract] ${truncated.length} chars of HTML`);
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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.
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The HTML uses semantic tags:
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- <table> with <thead>/<tbody> for structured tables (invoice line items, totals)
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- <header> for document header (company info, invoice number)
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- <footer> for document footer (payment terms, legal text)
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- <section class="table-region"> for table regions
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- data-type and data-y attributes indicate block type and vertical position
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Required fields:
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- invoice_number: The invoice/receipt/document number
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- invoice_date: Date in YYYY-MM-DD format (convert from any format)
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- vendor_name: Company that issued the invoice
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- currency: EUR, USD, GBP, etc.
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- net_amount: Amount before tax (number)
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- vat_amount: Tax/VAT amount (number, use 0 if reverse charge or not shown)
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- total_amount: Final total amount (number)
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Example output format:
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{"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}
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Rules:
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- Return ONLY the JSON object, no explanation or markdown
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- Use null for missing string fields
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- Use 0 for missing numeric fields
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- Convert dates to YYYY-MM-DD format (e.g., "28-JAN-2022" becomes "2022-01-28")
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- Extract numbers without currency symbols
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- Look for totals in <table> sections, especially rows with "Total", "Amount Due", "Grand Total"
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HTML Document:
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${truncated}
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JSON:`;
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const payload = {
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model: TEXT_MODEL,
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prompt,
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stream: true,
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options: {
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num_predict: 512,
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temperature: 0.1,
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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 response = await fetch(`${OLLAMA_URL}/api/generate`, {
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// Simple, direct prompt - the OCR output already has labeled fields
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const systemPrompt = `You read invoice HTML and extract labeled fields. Return JSON only.`;
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const userPrompt = `Extract from this invoice HTML:
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- invoice_number: Find "Invoice no.", "Invoice #", "Invoice", "Rechnung", "Document No" and extract the value
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- invoice_date: Find "Invoice date", "Date", "Datum" and convert to YYYY-MM-DD format
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- vendor_name: The company name issuing the invoice (in header/letterhead)
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- currency: EUR, USD, or GBP (look for € $ £ symbols or text)
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- total_amount: Find "Total", "Grand Total", "Amount Due", "Gesamtbetrag" - the FINAL total amount
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- net_amount: Amount before VAT/tax (Subtotal, Net)
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- vat_amount: VAT/tax amount
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HTML:
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${truncated}
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Return ONLY valid JSON: {"invoice_number":"...", "invoice_date":"YYYY-MM-DD", "vendor_name":"...", "currency":"EUR", "net_amount":0, "vat_amount":0, "total_amount":0}`;
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const response = await fetch(`${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(payload),
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body: JSON.stringify({
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model: TEXT_MODEL,
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messages: [
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{ role: 'system', content: systemPrompt },
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{ role: 'user', content: userPrompt },
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],
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format: invoiceSchema,
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stream: true,
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options: { num_predict: 512, temperature: 0.0 },
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}),
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});
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if (!response.ok) {
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@@ -169,7 +179,9 @@ JSON:`;
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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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if (json.message?.content) {
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fullText += json.message.content;
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} else if (json.response) {
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fullText += json.response;
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}
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} catch {
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@@ -179,17 +191,37 @@ JSON:`;
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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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let jsonStr = fullText.trim();
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// Remove markdown code block if present
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if (jsonStr.startsWith('```json')) {
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jsonStr = jsonStr.slice(7);
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} else if (jsonStr.startsWith('```')) {
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jsonStr = jsonStr.slice(3);
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}
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if (jsonStr.endsWith('```')) {
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jsonStr = jsonStr.slice(0, -3);
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}
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jsonStr = jsonStr.trim();
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// Find JSON object 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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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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const parsed = JSON.parse(jsonStr);
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jsonStr = jsonStr.substring(startIdx, endIdx);
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// Ensure numeric fields are actually numbers
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let parsed;
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try {
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parsed = JSON.parse(jsonStr);
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} catch (e) {
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throw new Error(`Invalid JSON: ${jsonStr.substring(0, 200)}`);
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}
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// Normalize response to expected format
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return {
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invoice_number: parsed.invoice_number || null,
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invoice_date: parsed.invoice_date || null,
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@@ -203,14 +235,23 @@ JSON:`;
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/**
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* Single extraction pass: Parse with PaddleOCR-VL Full, extract with Qwen2.5 (text-only)
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* Processes ALL pages and concatenates HTML for multi-page invoice support
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*/
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async function extractOnce(images: string[], passNum: number): Promise<IInvoice> {
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// Parse document with full pipeline (PaddleOCR-VL) -> returns HTML
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const html = await parseDocument(images[0]);
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console.log(` [Parse] Got ${html.split('\n').length} lines of HTML`);
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// Parse ALL pages and concatenate HTML with page markers
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const htmlParts: string[] = [];
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for (let i = 0; i < images.length; i++) {
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const pageHtml = await parseDocument(images[i]);
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// Add page marker for context
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htmlParts.push(`<!-- Page ${i + 1} -->\n${pageHtml}`);
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}
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const fullHtml = htmlParts.join('\n\n');
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console.log(` [Parse] Got ${fullHtml.split('\n').length} lines from ${images.length} page(s)`);
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// Extract invoice fields from HTML using text-only model (no images)
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return extractInvoiceFromHtml(html);
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return extractInvoiceFromHtml(fullHtml);
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}
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/**
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