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';

const OLLAMA_URL = 'http://localhost:11434';
const MODEL = 'openbmb/minicpm-v4.5:q8_0';
const PADDLEOCR_URL = 'http://localhost:5000';

// Prompt for visual extraction (with images)
const VISUAL_EXTRACT_PROMPT = `/nothink
You are a bank statement parser. Extract EVERY transaction from the table.

Read the Amount column carefully:
- "- 21,47 €" means DEBIT, output as: -21.47
- "+ 1.000,00 €" means CREDIT, output as: 1000.00
- European format: comma = decimal point

For each row output: {"date":"YYYY-MM-DD","counterparty":"NAME","amount":-21.47}

Do not skip any rows. Return ONLY the JSON array, no explanation.`;

// Prompt for OCR-only extraction (no images)
const OCR_EXTRACT_PROMPT = `/nothink
You are a bank statement parser. Extract EVERY transaction from the OCR text below.

Read the Amount values carefully:
- "- 21,47 €" means DEBIT, output as: -21.47
- "+ 1.000,00 €" means CREDIT, output as: 1000.00
- European format: comma = decimal point

For each transaction output: {"date":"YYYY-MM-DD","counterparty":"NAME","amount":-21.47}

Do not skip any transactions. Return ONLY the JSON array, no explanation.`;

/**
 * Build prompt for OCR-only extraction (no images)
 */
function buildOcrOnlyPrompt(ocrText: string): string {
  // Limit OCR text to prevent context overflow
  const maxOcrLength = 12000;
  const truncatedOcr = ocrText.length > maxOcrLength
    ? ocrText.substring(0, maxOcrLength) + '\n... (truncated)'
    : ocrText;

  return `${OCR_EXTRACT_PROMPT}

OCR text from bank statement:
---
${truncatedOcr}
---`;
}

/**
 * Extract OCR text from an image using PaddleOCR
 */
async function extractOcrText(imageBase64: string): Promise<string> {
  try {
    const response = await fetch(`${PADDLEOCR_URL}/ocr`, {
      method: 'POST',
      headers: { 'Content-Type': 'application/json' },
      body: JSON.stringify({ image: imageBase64 }),
    });

    if (!response.ok) return '';

    const data = await response.json();
    if (data.success && data.results) {
      return data.results.map((r: { text: string }) => r.text).join('\n');
    }
  } catch {
    // PaddleOCR unavailable
  }
  return '';
}

interface ITransaction {
  date: string;
  counterparty: string;
  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 300 -quality 100 "${pdfPath}" -background white -alpha remove "${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 });
  }
}

/**
 * Visual extraction pass (with images)
 */
async function extractVisual(images: string[], passLabel: string): Promise<ITransaction[]> {
  const payload = {
    model: MODEL,
    prompt: VISUAL_EXTRACT_PROMPT,
    images,
    stream: true,
    options: {
      num_predict: 16384,
      temperature: 0.1,
    },
  };

  return doExtraction(payload, passLabel);
}

/**
 * OCR-only extraction pass (no images, just text)
 */
async function extractFromOcr(ocrText: string, passLabel: string): Promise<ITransaction[]> {
  const payload = {
    model: MODEL,
    prompt: buildOcrOnlyPrompt(ocrText),
    stream: true,
    options: {
      num_predict: 16384,
      temperature: 0.1,
    },
  };

  return doExtraction(payload, passLabel);
}

/**
 * Common extraction logic
 */
async function doExtraction(payload: object, passLabel: string): Promise<ITransaction[]> {

  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 = '';
  let lineBuffer = '';

  console.log(`[${passLabel}] Extracting...`);

  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;
          lineBuffer += json.response;

          // Print complete lines
          if (lineBuffer.includes('\n')) {
            const parts = lineBuffer.split('\n');
            for (let i = 0; i < parts.length - 1; i++) {
              console.log(parts[i]);
            }
            lineBuffer = parts[parts.length - 1];
          }
        }
      } catch {
        // Skip invalid JSON lines
      }
    }
  }

  if (lineBuffer) {
    console.log(lineBuffer);
  }
  console.log('');

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

  if (startIdx < 0 || endIdx <= startIdx) {
    throw new Error('No JSON array found in response');
  }

  return JSON.parse(fullText.substring(startIdx, endIdx));
}

/**
 * Create a hash of transactions for comparison
 */
function hashTransactions(transactions: ITransaction[]): string {
  return transactions
    .map((t) => `${t.date}|${t.amount.toFixed(2)}`)
    .sort()
    .join(';');
}

/**
 * Extract with majority voting - run until 2 passes match
 * Strategy: Pass 1 = Visual (images), Pass 2 = OCR-only (text), Pass 3+ = Visual
 */
async function extractWithConsensus(images: string[], maxPasses: number = 5): Promise<ITransaction[]> {
  const results: Array<{ transactions: ITransaction[]; hash: string }> = [];
  const hashCounts: Map<string, number> = new Map();

  const addResult = (transactions: ITransaction[], passLabel: string): number => {
    const hash = hashTransactions(transactions);
    results.push({ transactions, hash });
    hashCounts.set(hash, (hashCounts.get(hash) || 0) + 1);
    console.log(`[${passLabel}] Got ${transactions.length} transactions (hash: ${hash.substring(0, 20)}...)`);
    return hashCounts.get(hash)!;
  };

  // Run Pass 1 (Visual) in parallel with OCR extraction
  let ocrText = '';
  const pass1Promise = extractVisual(images, 'Pass 1 Visual').catch((err) => ({ error: err }));

  // Extract OCR from all pages
  const ocrPromise = (async () => {
    const ocrTexts: string[] = [];
    for (let i = 0; i < images.length; i++) {
      const pageOcr = await extractOcrText(images[i]);
      if (pageOcr) {
        ocrTexts.push(`--- Page ${i + 1} ---\n${pageOcr}`);
      }
    }
    ocrText = ocrTexts.join('\n\n');
    if (ocrText) {
      console.log(`[OCR] Extracted text from ${ocrTexts.length} page(s)`);
    }
    return ocrText;
  })();

  // Wait for Pass 1 and OCR to complete
  const [pass1Result] = await Promise.all([pass1Promise, ocrPromise]);

  // Process Pass 1 result
  if ('error' in pass1Result) {
    console.log(`[Pass 1] Error: ${(pass1Result as { error: unknown }).error}`);
  } else {
    addResult(pass1Result as ITransaction[], 'Pass 1 Visual');
  }

  // Pass 2: OCR-only (no images) - faster, different approach
  if (ocrText) {
    try {
      const pass2Result = await extractFromOcr(ocrText, 'Pass 2 OCR-only');
      const count = addResult(pass2Result, 'Pass 2 OCR-only');
      if (count >= 2) {
        console.log(`[Consensus] Visual and OCR extractions match!`);
        return pass2Result;
      }
    } catch (err) {
      console.log(`[Pass 2 OCR-only] Error: ${err}`);
    }
  }

  // Continue with visual passes 3+ if no consensus yet
  for (let pass = 3; pass <= maxPasses; pass++) {
    try {
      const transactions = await extractVisual(images, `Pass ${pass} Visual`);
      const count = addResult(transactions, `Pass ${pass} Visual`);

      if (count >= 2) {
        console.log(`[Consensus] Reached after ${pass} passes`);
        return transactions;
      }

      console.log(`[Pass ${pass}] No consensus yet, trying again...`);
    } 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 obtained');
  }

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

/**
 * Compare extracted transactions against expected
 */
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 all test cases (PDF + JSON pairs) 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 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),
      });
    }
  }

  return testCases;
}

// Tests

tap.test('should connect to Ollama API', async () => {
  const response = await fetch(`${OLLAMA_URL}/api/tags`);
  expect(response.ok).toBeTrue();
  const data = await response.json();
  expect(data.models).toBeArray();
});

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

    // Convert PDF to images
    console.log('Converting PDF to images...');
    const images = convertPdfToImages(testCase.pdfPath);
    console.log(`Converted: ${images.length} pages\n`);

    // Extract with consensus voting
    const extracted = await extractWithConsensus(images);
    console.log(`\nFinal: ${extracted.length} transactions`);

    // Compare results
    const result = compareTransactions(extracted, expected);
    console.log(`Accuracy: ${result.matches}/${result.total}`);

    if (result.errors.length > 0) {
      console.log('Errors:');
      result.errors.forEach((e) => console.log(`  - ${e}`));
    }

    // Assert high accuracy
    const accuracy = result.matches / result.total;
    expect(accuracy).toBeGreaterThan(0.95);
    expect(extracted.length).toEqual(expected.length);
  });
}

export default tap.start();