ht-docker-ai/test/test.invoices.paddleocr-vl.ts

/**
 * Invoice extraction test using PaddleOCR-VL Full Pipeline
 *
 * This tests the complete PaddleOCR-VL pipeline:
 *   1. PP-DocLayoutV2 for layout detection
 *   2. PaddleOCR-VL for recognition
 *   3. Structured HTML output (semantic tags with proper tables)
 *   4. Qwen2.5 extracts invoice fields from structured HTML
 *
 * HTML output is used instead of Markdown because:
 * - <table> tags are unambiguous (no parser variations)
 * - LLMs are heavily trained on web/HTML data
 * - Semantic tags (header, footer, section) provide clear structure
 */
import { tap, expect } from '@git.zone/tstest/tapbundle';
import * as fs from 'fs';
import * as path from 'path';
import { execSync } from 'child_process';
import * as os from 'os';
import { ensurePaddleOcrVlFull, ensureQwen25 } from './helpers/docker.js';

const PADDLEOCR_VL_URL = 'http://localhost:8000';
const OLLAMA_URL = 'http://localhost:11434';
// Use Qwen2.5 for text-only JSON extraction (not MiniCPM which is vision-focused)
const TEXT_MODEL = 'qwen2.5:7b';

interface IInvoice {
  invoice_number: string;
  invoice_date: string;
  vendor_name: string;
  currency: string;
  net_amount: number;
  vat_amount: number;
  total_amount: number;
}

/**
 * Convert PDF to PNG images using ImageMagick
 */
function convertPdfToImages(pdfPath: string): string[] {
  const tempDir = fs.mkdtempSync(path.join(os.tmpdir(), 'pdf-convert-'));
  const outputPattern = path.join(tempDir, 'page-%d.png');

  try {
    execSync(
      `convert -density 200 -quality 90 "${pdfPath}" -background white -alpha remove "${outputPattern}"`,
      { stdio: 'pipe' }
    );

    const files = fs.readdirSync(tempDir).filter((f) => f.endsWith('.png')).sort();
    const images: string[] = [];

    for (const file of files) {
      const imagePath = path.join(tempDir, file);
      const imageData = fs.readFileSync(imagePath);
      images.push(imageData.toString('base64'));
    }

    return images;
  } finally {
    fs.rmSync(tempDir, { recursive: true, force: true });
  }
}

/**
 * Parse document using PaddleOCR-VL Full Pipeline (returns structured HTML)
 */
async function parseDocument(imageBase64: string): Promise<string> {
  const response = await fetch(`${PADDLEOCR_VL_URL}/parse`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      image: imageBase64,
      output_format: 'html',
    }),
  });

  if (!response.ok) {
    const text = await response.text();
    throw new Error(`PaddleOCR-VL API error: ${response.status} - ${text}`);
  }

  const data = await response.json();

  if (!data.success) {
    throw new Error(`PaddleOCR-VL error: ${data.error}`);
  }

  return data.result?.html || '';
}

/**
 * Extract invoice fields from structured HTML using Qwen2.5 (text-only model)
 */
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 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,
    },
  };

  const response = await fetch(`${OLLAMA_URL}/api/generate`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify(payload),
  });

  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.response) {
          fullText += json.response;
        }
      } catch {
        // Skip invalid JSON lines
      }
    }
  }

  // Extract JSON from response
  const startIdx = fullText.indexOf('{');
  const endIdx = fullText.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);

  // Ensure numeric fields are actually numbers
  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,
  };
}

/**
 * Single extraction pass: Parse with PaddleOCR-VL Full, extract with Qwen2.5 (text-only)
 */
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`);

  // Extract invoice fields from HTML using text-only model (no images)
  return extractInvoiceFromHtml(html);
}

/**
 * Create a hash of invoice for comparison (using key fields)
 */
function hashInvoice(invoice: IInvoice): string {
  // Ensure total_amount is a number
  const amount = typeof invoice.total_amount === 'number'
    ? invoice.total_amount.toFixed(2)
    : String(invoice.total_amount || 0);
  return `${invoice.invoice_number}|${invoice.invoice_date}|${amount}`;
}

/**
 * Extract with consensus voting
 */
async function extractWithConsensus(images: string[], invoiceName: string, maxPasses: number = 5): Promise<IInvoice> {
  const results: Array<{ invoice: IInvoice; hash: string }> = [];
  const hashCounts: Map<string, number> = new Map();

  const addResult = (invoice: IInvoice, passLabel: string): number => {
    const hash = hashInvoice(invoice);
    results.push({ invoice, hash });
    hashCounts.set(hash, (hashCounts.get(hash) || 0) + 1);
    console.log(`  [${passLabel}] ${invoice.invoice_number} | ${invoice.invoice_date} | ${invoice.total_amount} ${invoice.currency}`);
    return hashCounts.get(hash)!;
  };

  for (let pass = 1; pass <= maxPasses; pass++) {
    try {
      const invoice = await extractOnce(images, pass);
      const count = addResult(invoice, `Pass ${pass}`);

      if (count >= 2) {
        console.log(`  [Consensus] Reached after ${pass} passes`);
        return invoice;
      }
    } catch (err) {
      console.log(`  [Pass ${pass}] Error: ${err}`);
    }
  }

  // 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;
    }
  }

  if (!bestHash) {
    throw new Error(`No valid results for ${invoiceName}`);
  }

  const best = results.find((r) => r.hash === bestHash)!;
  console.log(`  [No consensus] Using most common result (${bestCount}/${maxPasses} passes)`);
  return best.invoice;
}

/**
 * Normalize date to YYYY-MM-DD format
 */
function normalizeDate(dateStr: string | null): string {
  if (!dateStr) return '';

  // Already in correct format
  if (/^\d{4}-\d{2}-\d{2}$/.test(dateStr)) {
    return dateStr;
  }

  // Handle DD-MMM-YYYY format (e.g., "28-JUN-2022")
  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',
  };

  const match = dateStr.match(/^(\d{1,2})-([A-Z]{3})-(\d{4})$/i);
  if (match) {
    const day = match[1].padStart(2, '0');
    const month = monthMap[match[2].toUpperCase()] || '01';
    const year = match[3];
    return `${year}-${month}-${day}`;
  }

  // Handle DD/MM/YYYY or DD.MM.YYYY
  const match2 = dateStr.match(/^(\d{1,2})[\/.](\d{1,2})[\/.](\d{4})$/);
  if (match2) {
    const day = match2[1].padStart(2, '0');
    const month = match2[2].padStart(2, '0');
    const year = match2[3];
    return `${year}-${month}-${day}`;
  }

  return dateStr;
}

/**
 * Compare extracted invoice against expected
 */
function compareInvoice(
  extracted: IInvoice,
  expected: IInvoice
): { match: boolean; errors: string[] } {
  const errors: string[] = [];

  // Compare invoice number (normalize by removing spaces and case)
  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}"`);
  }

  // Compare date (normalize format first)
  const extDate = normalizeDate(extracted.invoice_date);
  const expDate = normalizeDate(expected.invoice_date);
  if (extDate !== expDate) {
    errors.push(`invoice_date: expected "${expected.invoice_date}", got "${extracted.invoice_date}"`);
  }

  // Compare total amount (with tolerance)
  if (Math.abs(extracted.total_amount - expected.total_amount) > 0.02) {
    errors.push(`total_amount: expected ${expected.total_amount}, got ${extracted.total_amount}`);
  }

  // Compare currency
  if (extracted.currency?.toUpperCase() !== expected.currency?.toUpperCase()) {
    errors.push(`currency: expected "${expected.currency}", got "${extracted.currency}"`);
  }

  return { match: errors.length === 0, errors };
}

/**
 * Find all test cases (PDF + JSON pairs) in .nogit/invoices/
 */
function findTestCases(): Array<{ name: string; pdfPath: string; jsonPath: string }> {
  const testDir = path.join(process.cwd(), '.nogit/invoices');
  if (!fs.existsSync(testDir)) {
    return [];
  }

  const files = fs.readdirSync(testDir);
  const pdfFiles = files.filter((f) => f.endsWith('.pdf'));
  const testCases: Array<{ name: string; pdfPath: string; jsonPath: string }> = [];

  for (const pdf of pdfFiles) {
    const baseName = pdf.replace('.pdf', '');
    const jsonFile = `${baseName}.json`;
    if (files.includes(jsonFile)) {
      testCases.push({
        name: baseName,
        pdfPath: path.join(testDir, pdf),
        jsonPath: path.join(testDir, jsonFile),
      });
    }
  }

  // Sort alphabetically
  testCases.sort((a, b) => a.name.localeCompare(b.name));

  return testCases;
}

// Tests

tap.test('setup: ensure Docker containers are running', async () => {
  console.log('\n[Setup] Checking Docker containers...\n');

  // Ensure PaddleOCR-VL Full Pipeline is running
  const paddleOk = await ensurePaddleOcrVlFull();
  expect(paddleOk).toBeTrue();

  // Ensure Qwen2.5 is available (for text-only JSON extraction)
  const qwenOk = await ensureQwen25();
  expect(qwenOk).toBeTrue();

  console.log('\n[Setup] All containers ready!\n');
});

// Dynamic test for each PDF/JSON pair
const testCases = findTestCases();
console.log(`\nFound ${testCases.length} invoice test cases (PaddleOCR-VL Full Pipeline)\n`);

let passedCount = 0;
let failedCount = 0;
const processingTimes: number[] = [];

for (const testCase of testCases) {
  tap.test(`should extract invoice: ${testCase.name}`, async () => {
    // Load expected data
    const expected: IInvoice = JSON.parse(fs.readFileSync(testCase.jsonPath, 'utf-8'));
    console.log(`\n=== ${testCase.name} ===`);
    console.log(`Expected: ${expected.invoice_number} | ${expected.invoice_date} | ${expected.total_amount} ${expected.currency}`);

    const startTime = Date.now();

    // Convert PDF to images
    const images = convertPdfToImages(testCase.pdfPath);
    console.log(`  Pages: ${images.length}`);

    // Extract with consensus voting (PaddleOCR-VL Full -> MiniCPM)
    const extracted = await extractWithConsensus(images, testCase.name);

    const endTime = Date.now();
    const elapsedMs = endTime - startTime;
    processingTimes.push(elapsedMs);

    // Compare results
    const result = compareInvoice(extracted, expected);

    if (result.match) {
      passedCount++;
      console.log(`  Result: MATCH (${(elapsedMs / 1000).toFixed(1)}s)`);
    } else {
      failedCount++;
      console.log(`  Result: MISMATCH (${(elapsedMs / 1000).toFixed(1)}s)`);
      result.errors.forEach((e) => console.log(`    - ${e}`));
    }

    // Assert match
    expect(result.match).toBeTrue();
  });
}

tap.test('summary', async () => {
  const totalInvoices = testCases.length;
  const accuracy = totalInvoices > 0 ? (passedCount / totalInvoices) * 100 : 0;
  const totalTimeMs = processingTimes.reduce((a, b) => a + b, 0);
  const avgTimeMs = processingTimes.length > 0 ? totalTimeMs / processingTimes.length : 0;
  const avgTimeSec = avgTimeMs / 1000;
  const totalTimeSec = totalTimeMs / 1000;

  console.log(`\n======================================================`);
  console.log(`   Invoice Extraction Summary (PaddleOCR-VL Full)`);
  console.log(`======================================================`);
  console.log(`  Method:    PaddleOCR-VL Full Pipeline (HTML) -> Qwen2.5 (text-only)`);
  console.log(`  Passed:    ${passedCount}/${totalInvoices}`);
  console.log(`  Failed:    ${failedCount}/${totalInvoices}`);
  console.log(`  Accuracy:  ${accuracy.toFixed(1)}%`);
  console.log(`------------------------------------------------------`);
  console.log(`  Total time:   ${totalTimeSec.toFixed(1)}s`);
  console.log(`  Avg per inv:  ${avgTimeSec.toFixed(1)}s`);
  console.log(`======================================================\n`);
});

export default tap.start();