/**
 * POST /v1/score — Riskpoängsättning
 * Beräknar riskpoäng baserat på bildanalys + metadata
 */
import { Router } from 'express';
import sharp from 'sharp';
import { fetchImage, hashInput, saveResult, genReqId, requireAuth } from './utils.mjs';

const router = Router();

async function analyzeImageRisk(buffer) {
  const { data, info } = await sharp(buffer).resize(128, 128).raw().toBuffer({ resolveWithObject: true });
  const w = info.width, h = info.height;
  
  // Analyze image quality metrics
  let totalBrightness = 0, totalContrast = 0, edgeCount = 0;
  const brightnessHistogram = new Array(256).fill(0);
  
  for (let y = 0; y < h; y++) {
    for (let x = 0; x < w; x++) {
      const i = (y * w + x) * 3;
      const gray = (data[i] + data[i+1] + data[i+2]) / 3;
      totalBrightness += gray;
      brightnessHistogram[Math.round(gray)]++;
      
      if (x < w - 1) {
        const diff = Math.abs(gray - ((data[i+3] + data[i+4] + data[i+5]) / 3));
        totalContrast += diff;
        if (diff > 30) edgeCount++;
      }
    }
  }
  
  const pixelCount = w * h;
  const avgBrightness = totalBrightness / pixelCount;
  const avgContrast = totalContrast / pixelCount;
  const edgeRatio = edgeCount / pixelCount;
  
  // Calculate entropy (measure of randomness/complexity)
  let entropy = 0;
  for (let i = 0; i < 256; i++) {
    const p = brightnessHistogram[i] / pixelCount;
    if (p > 0) entropy -= p * Math.log2(p);
  }
  
  return {
    brightness: Math.round(avgBrightness),
    contrast: Math.round(avgContrast),
    edge_ratio: parseFloat(edgeRatio.toFixed(4)),
    entropy: parseFloat(entropy.toFixed(4)),
    dark_ratio: parseFloat((brightnessHistogram.slice(0, 50).reduce((a,b)=>a+b,0) / pixelCount).toFixed(4)),
    bright_ratio: parseFloat((brightnessHistogram.slice(200).reduce((a,b)=>a+b,0) / pixelCount).toFixed(4)),
  };
}

function calculateRiskScore(analysis, metadata = {}) {
  let score = 0.3; // Base risk
  const factors = [];
  
  // Image quality risks
  if (analysis.brightness < 30) { score += 0.15; factors.push({ type: 'image', reason: 'Very dark image', contribution: 0.15 }); }
  if (analysis.brightness > 240) { score += 0.1; factors.push({ type: 'image', reason: 'Overexposed image', contribution: 0.1 }); }
  if (analysis.contrast < 5) { score += 0.2; factors.push({ type: 'image', reason: 'Low contrast — possible synthetic image', contribution: 0.2 }); }
  if (analysis.entropy < 3) { score += 0.15; factors.push({ type: 'image', reason: 'Low entropy — possible compression artifact or synthetic', contribution: 0.15 }); }
  if (analysis.edge_ratio < 0.02) { score += 0.1; factors.push({ type: 'image', reason: 'Few edges — possibly blurred or artificial', contribution: 0.1 }); }
  
  // Metadata risks
  if (metadata.source === 'base64' && !metadata.filename) { score += 0.05; factors.push({ type: 'metadata', reason: 'No filename metadata', contribution: 0.05 }); }
  if (metadata.user_agent && metadata.user_agent.includes('bot')) { score += 0.1; factors.push({ type: 'metadata', reason: 'Bot user agent', contribution: 0.1 }); }
  
  // Time-based risks
  const hour = new Date().getUTCHours();
  if (hour < 5 || hour > 22) { score += 0.05; factors.push({ type: 'time', reason: 'Unusual request hour', contribution: 0.05 }); }
  
  return {
    score: parseFloat(Math.min(1.0, score).toFixed(4)),
    factors: factors.slice(0, 5),
    analysis,
  };
}

router.post('/', requireAuth, async (req, res) => {
  const requestId = genReqId();
  const start = Date.now();
  try {
    const { image_url, image_base64, metadata = {} } = req.body || {};
    const img = await fetchImage({ image_url, image_base64 });
    const inputHash = hashInput(img.buffer);

    const analysis = await analyzeImageRisk(img.buffer);
    const risk = calculateRiskScore(analysis, { ...metadata, source: img.source });

    const result = {
      ok: true,
      endpoint: 'score',
      request_id: requestId,
      risk_score: risk.score,
      risk_level: risk.score > 0.7 ? 'high' : risk.score > 0.4 ? 'medium' : 'low',
      confidence: parseFloat((1 - risk.score * 0.3).toFixed(4)),
      factors: risk.factors,
      image_analysis: risk.analysis,
      recommendations: risk.score > 0.7 
        ? ['Require additional verification', 'Flag for manual review', 'Check device fingerprint']
        : risk.score > 0.4
        ? ['Standard verification recommended', 'Monitor for anomalies']
        : ['Low risk — standard processing'],
      inference_time_ms: Date.now() - start,
    };

    await saveResult('score', requestId, inputHash, result, result.confidence, { source: img.source, metadata });
    res.json(result);
  } catch (e) {
    console.error('[score]', e);
    res.status(500).json({ ok: false, error: e.message, request_id: requestId });
  }
});

export default router;