/**
 * Invoice extraction test using MiniCPM-V (visual) + PaddleOCR-VL (OCR augmentation)
 *
 * This is the combined approach that uses both models for best accuracy:
 *   - MiniCPM-V for visual understanding
 *   - PaddleOCR-VL for OCR text to augment prompts
 */
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 { ensurePaddleOcrVl, ensureMiniCpm } from './helpers/docker.js';

const OLLAMA_URL = 'http://localhost:11434';
const MODEL = 'minicpm-v:latest';
const PADDLEOCR_VL_URL = 'http://localhost:8000';

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

/**
 * Extract OCR text from an image using PaddleOCR-VL (OpenAI-compatible API)
 */
async function extractOcrText(imageBase64: string): Promise<string> {
  try {
    const response = await fetch(`${PADDLEOCR_VL_URL}/v1/chat/completions`, {
      method: 'POST',
      headers: { 'Content-Type': 'application/json' },
      body: JSON.stringify({
        model: 'paddleocr-vl',
        messages: [{
          role: 'user',
          content: [
            { type: 'image_url', image_url: { url: `data:image/png;base64,${imageBase64}` } },
            { type: 'text', text: 'OCR:' }
          ]
        }],
        temperature: 0.0,
        max_tokens: 4096
      }),
    });

    if (!response.ok) return '';

    const data = await response.json();
    return data.choices?.[0]?.message?.content || '';
  } catch {
    // PaddleOCR-VL unavailable
  }
  return '';
}

/**
 * Build prompt with optional OCR text
 */
function buildPrompt(ocrText: string): string {
  const base = `/nothink
You are an invoice parser. Extract the following fields from this invoice:

1. invoice_number: The invoice/receipt number
2. invoice_date: Date in YYYY-MM-DD format
3. vendor_name: Company that issued the invoice
4. currency: EUR, USD, etc.
5. net_amount: Amount before tax (if shown)
6. vat_amount: Tax/VAT amount (if shown, 0 if reverse charge or no tax)
7. total_amount: Final amount due

Return ONLY valid JSON in this exact format:
{"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}

If a field is not visible, use null for strings or 0 for numbers.
No explanation, just the JSON object.`;

  if (ocrText) {
    // Limit OCR text to prevent context overflow
    const maxOcrLength = 4000;
    const truncatedOcr = ocrText.length > maxOcrLength
      ? ocrText.substring(0, maxOcrLength) + '\n... (truncated)'
      : ocrText;

    return `${base}

OCR text extracted from the invoice (use for reference):
---
${truncatedOcr}
---

Cross-reference the image with the OCR text above for accuracy.`;
  }
  return base;
}

/**
 * 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 });
  }
}

/**
 * Single extraction pass
 */
async function extractOnce(images: string[], passNum: number, ocrText: string = ''): Promise<IInvoice> {
  const payload = {
    model: MODEL,
    prompt: buildPrompt(ocrText),
    images,
    stream: true,
    options: {
      num_predict: 2048,
      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);
  return JSON.parse(jsonStr);
}

/**
 * Create a hash of invoice for comparison (using key fields)
 */
function hashInvoice(invoice: IInvoice): string {
  return `${invoice.invoice_number}|${invoice.invoice_date}|${invoice.total_amount.toFixed(2)}`;
}

/**
 * Extract with majority voting - run until 2 passes match
 * Optimization: Run Pass 1, OCR, and Pass 2 (after OCR) in parallel
 */
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)!;
  };

  // OPTIMIZATION: Run Pass 1 (no OCR) in parallel with OCR -> Pass 2 (with OCR)
  let ocrText = '';
  const pass1Promise = extractOnce(images, 1, '').catch((err) => ({ error: err }));

  // OCR then immediately Pass 2
  const ocrThenPass2Promise = (async () => {
    ocrText = await extractOcrText(images[0]);
    if (ocrText) {
      console.log(`  [OCR] Extracted ${ocrText.split('\n').length} text lines`);
    }
    return extractOnce(images, 2, ocrText).catch((err) => ({ error: err }));
  })();

  // Wait for both to complete
  const [pass1Result, pass2Result] = await Promise.all([pass1Promise, ocrThenPass2Promise]);

  // Process Pass 1 result
  if ('error' in pass1Result) {
    console.log(`  [Pass 1] Error: ${(pass1Result as {error: unknown}).error}`);
  } else {
    const count = addResult(pass1Result as IInvoice, 'Pass 1');
    if (count >= 2) {
      console.log(`  [Consensus] Reached after parallel passes`);
      return pass1Result as IInvoice;
    }
  }

  // Process Pass 2 result
  if ('error' in pass2Result) {
    console.log(`  [Pass 2+OCR] Error: ${(pass2Result as {error: unknown}).error}`);
  } else {
    const count = addResult(pass2Result as IInvoice, 'Pass 2+OCR');
    if (count >= 2) {
      console.log(`  [Consensus] Reached after parallel passes`);
      return pass2Result as IInvoice;
    }
  }

  // Continue with passes 3+ using OCR text if no consensus yet
  for (let pass = 3; pass <= maxPasses; pass++) {
    try {
      const invoice = await extractOnce(images, pass, ocrText);
      const count = addResult(invoice, `Pass ${pass}+OCR`);

      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;
}

/**
 * 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
  if (extracted.invoice_date !== expected.invoice_date) {
    errors.push(`invoice_date: expected "${expected.invoice_date}", got "${extracted.invoice_date}"`);
  }

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

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

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

/**
 * Find all test cases (PDF + JSON pairs) in .nogit/invoices/
 * Priority invoices (like vodafone) run first for quick feedback
 */
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 with priority invoices first, then alphabetically
  const priorityPrefixes = ['vodafone'];
  testCases.sort((a, b) => {
    const aPriority = priorityPrefixes.findIndex((p) => a.name.startsWith(p));
    const bPriority = priorityPrefixes.findIndex((p) => b.name.startsWith(p));

    // Both have priority - sort by priority order
    if (aPriority >= 0 && bPriority >= 0) return aPriority - bPriority;
    // Only a has priority - a comes first
    if (aPriority >= 0) return -1;
    // Only b has priority - b comes first
    if (bPriority >= 0) return 1;
    // Neither has priority - alphabetical
    return 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 is running (auto-detects GPU/CPU)
  const paddleOk = await ensurePaddleOcrVl();
  expect(paddleOk).toBeTrue();

  // Ensure MiniCPM is running
  const minicpmOk = await ensureMiniCpm();
  expect(minicpmOk).toBeTrue();

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

tap.test('should have MiniCPM-V 4.5 model loaded', async () => {
  const response = await fetch(`${OLLAMA_URL}/api/tags`);
  const data = await response.json();
  const modelNames = data.models.map((m: { name: string }) => m.name);
  expect(modelNames.some((name: string) => name.includes('minicpm-v4.5'))).toBeTrue();
});

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