/**
 * Bank statement extraction using Qwen3-VL 8B Vision (Direct)
 *
 * Single-step pipeline: PDF → Images → Qwen3-VL → JSON
 *
 * Key insights:
 * - Use /no_think in prompt + think:false in API to disable reasoning
 * - Need high num_predict (8000+) for many transactions
 * - Single pass extraction, no consensus needed
 */
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 { ensureMiniCpm } from './helpers/docker.js';

const OLLAMA_URL = 'http://localhost:11434';
const VISION_MODEL = 'qwen3-vl:8b';

interface ITransaction {
  date: string;
  counterparty: string;
  amount: number;
}

/**
 * Convert PDF to PNG images
 */
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 150 -quality 90 "${pdfPath}" -background white -alpha remove "${outputPattern}"`,
      { stdio: 'pipe' }
    );

    const files = fs.readdirSync(tempDir).filter((f: string) => 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 });
  }
}

/**
 * Extract transactions from a single page
 * Processes one page at a time to minimize thinking tokens
 */
async function extractTransactionsFromPage(image: string, pageNum: number): Promise<ITransaction[]> {
  const prompt = `/no_think
Extract transactions from this bank statement page.
Amount: "- 21,47 €" = -21.47, "+ 1.000,00 €" = 1000.00 (European format)
Return JSON array only: [{"date":"YYYY-MM-DD","counterparty":"NAME","amount":-21.47},...]`;

  const response = await fetch(`${OLLAMA_URL}/api/chat`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      model: VISION_MODEL,
      messages: [{
        role: 'user',
        content: prompt,
        images: [image],
      }],
      stream: false,
      think: false,
      options: {
        num_predict: 4000,
        temperature: 0.1,
      },
    }),
  });

  if (!response.ok) {
    throw new Error(`Ollama API error: ${response.status}`);
  }

  const data = await response.json();
  let content = data.message?.content || '';

  if (!content) {
    console.log(`    [Page ${pageNum}] Empty response`);
    return [];
  }

  // Parse JSON array
  if (content.startsWith('```json')) content = content.slice(7);
  else if (content.startsWith('```')) content = content.slice(3);
  if (content.endsWith('```')) content = content.slice(0, -3);
  content = content.trim();

  const startIdx = content.indexOf('[');
  const endIdx = content.lastIndexOf(']') + 1;

  if (startIdx < 0 || endIdx <= startIdx) {
    console.log(`    [Page ${pageNum}] No JSON array found`);
    return [];
  }

  try {
    const transactions = JSON.parse(content.substring(startIdx, endIdx));
    console.log(`    [Page ${pageNum}] Found ${transactions.length} transactions`);
    return transactions;
  } catch {
    console.log(`    [Page ${pageNum}] JSON parse error`);
    return [];
  }
}

/**
 * Extract transactions using Qwen3-VL vision
 * Processes each page separately to avoid thinking token exhaustion
 */
async function extractTransactions(images: string[]): Promise<ITransaction[]> {
  console.log(`    [Vision] Processing ${images.length} page(s) with Qwen3-VL`);

  const allTransactions: ITransaction[] = [];

  // Process pages sequentially to avoid overwhelming the model
  for (let i = 0; i < images.length; i++) {
    const pageTransactions = await extractTransactionsFromPage(images[i], i + 1);
    allTransactions.push(...pageTransactions);
  }

  console.log(`    [Vision] Total: ${allTransactions.length} transactions`);
  return allTransactions;
}

/**
 * Compare transactions
 */
function compareTransactions(
  extracted: ITransaction[],
  expected: ITransaction[]
): { matches: number; total: number; errors: string[] } {
  const errors: string[] = [];
  let matches = 0;

  for (let i = 0; i < expected.length; i++) {
    const exp = expected[i];
    const ext = extracted[i];

    if (!ext) {
      errors.push(`Missing transaction ${i}: ${exp.date} ${exp.counterparty}`);
      continue;
    }

    const dateMatch = ext.date === exp.date;
    const amountMatch = Math.abs(ext.amount - exp.amount) < 0.01;

    if (dateMatch && amountMatch) {
      matches++;
    } else {
      errors.push(`Mismatch at ${i}: expected ${exp.date}/${exp.amount}, got ${ext.date}/${ext.amount}`);
    }
  }

  if (extracted.length > expected.length) {
    errors.push(`Extra transactions: ${extracted.length - expected.length}`);
  }

  return { matches, total: expected.length, errors };
}

/**
 * Find test cases in .nogit/
 */
function findTestCases(): Array<{ name: string; pdfPath: string; jsonPath: string }> {
  const testDir = path.join(process.cwd(), '.nogit');
  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: string) => 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));
}

/**
 * Ensure Qwen3-VL model is available
 */
async function ensureQwen3Vl(): Promise<boolean> {
  try {
    const response = await fetch(`${OLLAMA_URL}/api/tags`);
    if (response.ok) {
      const data = await response.json();
      const models = data.models || [];
      if (models.some((m: { name: string }) => m.name === VISION_MODEL)) {
        console.log(`[Ollama] Model available: ${VISION_MODEL}`);
        return true;
      }
    }
  } catch {
    return false;
  }

  console.log(`[Ollama] Pulling ${VISION_MODEL}...`);
  const pullResponse = await fetch(`${OLLAMA_URL}/api/pull`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({ name: VISION_MODEL, stream: false }),
  });

  return pullResponse.ok;
}

// Tests

tap.test('setup: ensure Qwen3-VL is running', async () => {
  console.log('\n[Setup] Checking Qwen3-VL 8B...\n');
  const ollamaOk = await ensureMiniCpm();
  expect(ollamaOk).toBeTrue();
  const visionOk = await ensureQwen3Vl();
  expect(visionOk).toBeTrue();
  console.log('\n[Setup] Ready!\n');
});

const testCases = findTestCases();
console.log(`\nFound ${testCases.length} bank statement test cases (Qwen3-VL)\n`);

let passedCount = 0;
let failedCount = 0;

for (const testCase of testCases) {
  tap.test(`should extract: ${testCase.name}`, async () => {
    const expected: ITransaction[] = JSON.parse(fs.readFileSync(testCase.jsonPath, 'utf-8'));
    console.log(`\n=== ${testCase.name} ===`);
    console.log(`Expected: ${expected.length} transactions`);

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

    const extracted = await extractTransactions(images);
    console.log(`  Extracted: ${extracted.length} transactions`);

    const result = compareTransactions(extracted, expected);
    const accuracy = result.total > 0 ? result.matches / result.total : 0;

    if (accuracy >= 0.95 && extracted.length === expected.length) {
      passedCount++;
      console.log(`  Result: PASS (${result.matches}/${result.total})`);
    } else {
      failedCount++;
      console.log(`  Result: FAIL (${result.matches}/${result.total})`);
      result.errors.slice(0, 5).forEach((e) => console.log(`    - ${e}`));
    }

    expect(accuracy).toBeGreaterThan(0.95);
    expect(extracted.length).toEqual(expected.length);
  });
}

tap.test('summary', async () => {
  const total = testCases.length;
  console.log(`\n======================================================`);
  console.log(`   Bank Statement Summary (Qwen3-VL Vision)`);
  console.log(`======================================================`);
  console.log(`  Passed: ${passedCount}/${total}`);
  console.log(`  Failed: ${failedCount}/${total}`);
  console.log(`======================================================\n`);
});

export default tap.start();