import { QwenImageEdit } from '@qwen/image-edit';

const client = new QwenImageEdit({
  apiKey: process.env.QWEN_API_KEY
});

// Batch edit multiple images
const batchEdit = async (images, prompt) => {
  const results = await Promise.allSettled(
    images.map(async (image, index) => {
      try {
        const result = await client.edit({
          image: image,
          prompt: prompt,
          // Add unique identifier for tracking
          metadata: { batchId: Date.now(), index }
        });
        return { success: true, result, index };
      } catch (error) {
        return { success: false, error, index };
      }
    })
  );
  
  return results;
};

// Usage
const images = [image1, image2, image3];
const results = await batchEdit(images, "Add vintage filter");

// Process results
results.forEach((result, index) => {
  if (result.status === 'fulfilled' && result.value.success) {
    console.log(`Image ${index} processed successfully`);
  } else {
    console.error(`Image ${index} failed:`, result.reason || result.value.error);
  }
});

class BatchProcessor {
  constructor(client, options = {}) {
    this.client = client;
    this.concurrency = options.concurrency || 3;
    this.delay = options.delay || 1000;
  }
  
  async processBatch(tasks) {
    const results = [];
    
    for (let i = 0; i < tasks.length; i += this.concurrency) {
      const batch = tasks.slice(i, i + this.concurrency);
      
      const batchResults = await Promise.allSettled(
        batch.map(task => this.processTask(task))
      );
      
      results.push(...batchResults);
      
      // Add delay between batches
      if (i + this.concurrency < tasks.length) {
        await new Promise(resolve => setTimeout(resolve, this.delay));
      }
    }
    
    return results;
  }
  
  async processTask(task) {
    return await this.client.edit(task);
  }
}

// Usage
const processor = new BatchProcessor(client, {
  concurrency: 2,
  delay: 500
});

const tasks = images.map(image => ({
  image,
  prompt: "Enhance image quality"
}));

const results = await processor.processBatch(tasks);

// Use a custom fine-tuned model
const result = await client.edit({
  image: inputImage,
  prompt: "Apply brand-specific styling",
  model: "custom-brand-model-v1",
  parameters: {
    strength: 0.8,
    guidance_scale: 7.5,
    custom_params: {
      brand_style: "modern",
      color_palette: "corporate"
    }
  }
});

class ModelSelector {
  constructor() {
    this.models = {
      'portrait': 'qwen-portrait-v2',
      'landscape': 'qwen-landscape-v2',
      'product': 'qwen-product-v1',
      'artistic': 'qwen-artistic-v3',
      'custom-brand': 'custom-brand-model-v1'
    };
  }
  
  selectModel(imageType, editType) {
    // Logic to select appropriate model
    if (editType === 'brand-styling') {
      return this.models['custom-brand'];
    }
    
    return this.models[imageType] || 'qwen-general-v2';
  }
}

const selector = new ModelSelector();
const model = selector.selectModel('portrait', 'enhancement');

const result = await client.edit({
  image: inputImage,
  prompt: "Enhance portrait lighting",
  model: model
});

class EditingPipeline {
  constructor(client) {
    this.client = client;
    this.steps = [];
  }
  
  addStep(prompt, options = {}) {
    this.steps.push({ prompt, options });
    return this;
  }
  
  async execute(inputImage) {
    let currentImage = inputImage;
    const results = [];
    
    for (const [index, step] of this.steps.entries()) {
      try {
        const result = await this.client.edit({
          image: currentImage,
          prompt: step.prompt,
          ...step.options
        });
        
        currentImage = result.image;
        results.push({
          step: index + 1,
          prompt: step.prompt,
          success: true,
          result
        });
      } catch (error) {
        results.push({
          step: index + 1,
          prompt: step.prompt,
          success: false,
          error
        });
        break;
      }
    }
    
    return {
      finalImage: currentImage,
      steps: results
    };
  }
}

// Usage
const pipeline = new EditingPipeline(client)
  .addStep("Remove background", { strength: 0.9 })
  .addStep("Add professional lighting", { strength: 0.7 })
  .addStep("Enhance colors", { strength: 0.6 });

const result = await pipeline.execute(inputImage);

const conditionalEdit = async (image, conditions) => {
  // Analyze image first
  const analysis = await client.analyze({
    image: image,
    features: ['objects', 'colors', 'composition']
  });
  
  let editPrompt = "";
  let editOptions = {};
  
  // Apply conditions based on analysis
  if (analysis.brightness < 0.3) {
    editPrompt += "Brighten the image, ";
    editOptions.strength = 0.8;
  }
  
  if (analysis.objects.includes('person')) {
    editPrompt += "enhance portrait features, ";
    editOptions.model = 'qwen-portrait-v2';
  }
  
  if (analysis.colors.saturation < 0.5) {
    editPrompt += "increase color saturation";
  }
  
  // Remove trailing comma and space
  editPrompt = editPrompt.replace(/, $/, '');
  
  return await client.edit({
    image: image,
    prompt: editPrompt,
    ...editOptions
  });
};

class ImageOptimizer {
  static async optimizeForEditing(image, options = {}) {
    const {
      maxWidth = 2048,
      maxHeight = 2048,
      quality = 0.9,
      format = 'jpeg'
    } = options;
    
    return new Promise((resolve) => {
      const canvas = document.createElement('canvas');
      const ctx = canvas.getContext('2d');
      const img = new Image();
      
      img.onload = () => {
        // Calculate optimal dimensions
        const ratio = Math.min(
          maxWidth / img.width,
          maxHeight / img.height,
          1 // Don't upscale
        );
        
        canvas.width = img.width * ratio;
        canvas.height = img.height * ratio;
        
        // Apply image smoothing
        ctx.imageSmoothingEnabled = true;
        ctx.imageSmoothingQuality = 'high';
        
        ctx.drawImage(img, 0, 0, canvas.width, canvas.height);
        
        canvas.toBlob(resolve, `image/${format}`, quality);
      };
      
      img.src = URL.createObjectURL(image);
    });
  }
}

// Usage
const optimizedImage = await ImageOptimizer.optimizeForEditing(originalImage, {
  maxWidth: 1024,
  quality: 0.85
});

const result = await client.edit({
  image: optimizedImage,
  prompt: "Professional photo enhancement"
});

class EditCache {
  constructor(maxSize = 100) {
    this.cache = new Map();
    this.maxSize = maxSize;
  }
  
  generateKey(image, prompt, options = {}) {
    // Create a hash of the input parameters
    const params = JSON.stringify({ prompt, options });
    return `${this.hashImage(image)}-${this.hashString(params)}`;
  }
  
  hashImage(image) {
    // Simple hash based on image size and type
    return `${image.size}-${image.type}-${image.lastModified || Date.now()}`;
  }
  
  hashString(str) {
    let hash = 0;
    for (let i = 0; i < str.length; i++) {
      const char = str.charCodeAt(i);
      hash = ((hash << 5) - hash) + char;
      hash = hash & hash; // Convert to 32-bit integer
    }
    return hash.toString();
  }
  
  get(key) {
    if (this.cache.has(key)) {
      // Move to end (LRU)
      const value = this.cache.get(key);
      this.cache.delete(key);
      this.cache.set(key, value);
      return value;
    }
    return null;
  }
  
  set(key, value) {
    if (this.cache.size >= this.maxSize) {
      // Remove oldest entry
      const firstKey = this.cache.keys().next().value;
      this.cache.delete(firstKey);
    }
    this.cache.set(key, value);
  }
}

// Usage with caching
const cache = new EditCache(50);

const cachedEdit = async (image, prompt, options = {}) => {
  const key = cache.generateKey(image, prompt, options);
  
  // Check cache first
  const cached = cache.get(key);
  if (cached) {
    console.log('Cache hit!');
    return cached;
  }
  
  // Process and cache result
  const result = await client.edit({ image, prompt, ...options });
  cache.set(key, result);
  
  return result;
};

// Set up webhook for async processing
const setupWebhook = async () => {
  await client.webhook.create({
    url: 'https://your-app.com/webhooks/qwen',
    events: ['edit.completed', 'edit.failed', 'batch.completed'],
    secret: process.env.WEBHOOK_SECRET
  });
};

// Handle webhook events
app.post('/webhooks/qwen', (req, res) => {
  const signature = req.headers['x-qwen-signature'];
  const payload = req.body;
  
  // Verify webhook signature
  if (!verifyWebhookSignature(payload, signature)) {
    return res.status(401).send('Invalid signature');
  }
  
  switch (payload.event) {
    case 'edit.completed':
      handleEditCompleted(payload.data);
      break;
    case 'edit.failed':
      handleEditFailed(payload.data);
      break;
    case 'batch.completed':
      handleBatchCompleted(payload.data);
      break;
  }
  
  res.status(200).send('OK');
});

class UsageTracker {
  constructor(client) {
    this.client = client;
    this.metrics = {
      totalEdits: 0,
      successfulEdits: 0,
      failedEdits: 0,
      totalProcessingTime: 0,
      averageProcessingTime: 0
    };
  }
  
  async trackEdit(editFunction) {
    const startTime = Date.now();
    
    try {
      const result = await editFunction();
      
      const processingTime = Date.now() - startTime;
      this.updateMetrics(true, processingTime);
      
      return result;
    } catch (error) {
      this.updateMetrics(false, Date.now() - startTime);
      throw error;
    }
  }
  
  updateMetrics(success, processingTime) {
    this.metrics.totalEdits++;
    this.metrics.totalProcessingTime += processingTime;
    
    if (success) {
      this.metrics.successfulEdits++;
    } else {
      this.metrics.failedEdits++;
    }
    
    this.metrics.averageProcessingTime = 
      this.metrics.totalProcessingTime / this.metrics.totalEdits;
  }
  
  getMetrics() {
    return {
      ...this.metrics,
      successRate: this.metrics.successfulEdits / this.metrics.totalEdits,
      failureRate: this.metrics.failedEdits / this.metrics.totalEdits
    };
  }
}

// Usage
const tracker = new UsageTracker(client);

const result = await tracker.trackEdit(async () => {
  return await client.edit({
    image: inputImage,
    prompt: "Professional enhancement"
  });
});

console.log('Usage metrics:', tracker.getMetrics());

// Secure API key rotation
class SecureClient {
  constructor(options) {
    this.primaryKey = options.primaryKey;
    this.backupKey = options.backupKey;
    this.keyRotationInterval = options.keyRotationInterval || 24 * 60 * 60 * 1000; // 24 hours
    this.lastRotation = Date.now();
  }
  
  getCurrentKey() {
    const now = Date.now();
    if (now - this.lastRotation > this.keyRotationInterval) {
      // Rotate keys
      [this.primaryKey, this.backupKey] = [this.backupKey, this.primaryKey];
      this.lastRotation = now;
    }
    return this.primaryKey;
  }
  
  async makeRequest(params) {
    try {
      return await this.client.edit({
        ...params,
        apiKey: this.getCurrentKey()
      });
    } catch (error) {
      if (error.status === 401) {
        // Try backup key
        return await this.client.edit({
          ...params,
          apiKey: this.backupKey
        });
      }
      throw error;
    }
  }
}

class SecureImageProcessor {
  static validateImage(file) {
    const maxSize = 10 * 1024 * 1024; // 10MB
    const allowedTypes = ['image/jpeg', 'image/png', 'image/webp'];
    
    if (file.size > maxSize) {
      throw new Error('File size exceeds maximum limit');
    }
    
    if (!allowedTypes.includes(file.type)) {
      throw new Error('Unsupported file type');
    }
    
    return true;
  }
  
  static sanitizePrompt(prompt) {
    // Remove potentially harmful content
    const sanitized = prompt
      .replace(/<script[^>]*>.*?<\/script>/gi, '')
      .replace(/javascript:/gi, '')
      .replace(/on\w+\s*=/gi, '')
      .trim();
    
    if (sanitized.length > 500) {
      throw new Error('Prompt too long');
    }
    
    return sanitized;
  }
}

class AdvancedLogger {
  constructor(options = {}) {
    this.logLevel = options.logLevel || 'info';
    this.enableMetrics = options.enableMetrics || false;
  }
  
  log(level, message, metadata = {}) {
    const logEntry = {
      timestamp: new Date().toISOString(),
      level,
      message,
      metadata,
      requestId: metadata.requestId || this.generateRequestId()
    };
    
    if (this.shouldLog(level)) {
      console.log(JSON.stringify(logEntry));
    }
    
    if (this.enableMetrics) {
      this.sendToMetrics(logEntry);
    }
  }
  
  shouldLog(level) {
    const levels = ['debug', 'info', 'warn', 'error'];
    return levels.indexOf(level) >= levels.indexOf(this.logLevel);
  }
  
  generateRequestId() {
    return Math.random().toString(36).substring(2, 15);
  }
  
  sendToMetrics(logEntry) {
    // Send to your metrics service
    // Implementation depends on your monitoring stack
  }
}

// Usage
const logger = new AdvancedLogger({ logLevel: 'info', enableMetrics: true });

const enhancedEdit = async (image, prompt, options = {}) => {
  const requestId = logger.generateRequestId();
  
  logger.log('info', 'Starting image edit', {
    requestId,
    imageSize: image.size,
    prompt: prompt.substring(0, 100)
  });
  
  try {
    const result = await client.edit({ image, prompt, ...options });
    
    logger.log('info', 'Image edit completed', {
      requestId,
      success: true,
      processingTime: result.processingTime
    });
    
    return result;
  } catch (error) {
    logger.log('error', 'Image edit failed', {
      requestId,
      error: error.message,
      stack: error.stack
    });
    
    throw error;
  }
};