Batch Processing for AI Video

const generateBatchImages = async (prompts, concurrency = 5) => {
  const results = [];
  // Process in chunks to respect rate limits
  for (let i = 0; i < prompts.length; i += concurrency) {
    const chunk = prompts.slice(i, i + concurrency);
    const promises = chunk.map(prompt =>
      openai.images.generate({
        model: 'dall-e-3',
        prompt: prompt,
        size: '1792x1024',
        quality: 'hd',
        n: 1
      })
    );
    const chunkResults = await Promise.allSettled(promises);
    results.push(...chunkResults);
    // Respect rate limits: pause between chunks
    if (i + concurrency < prompts.length) {
      await sleep(2000);
    }
  }
  return results;
};

// Generate 50 images in batches of 5
const allPrompts = scenes.map(s => s.visual_prompt);
const images = await generateBatchImages(allPrompts, 5);

const batchGenerateVideos = async (imageUrls, prompts) => {
  // Step 1: Submit all generation tasks
  const tasks = [];
  for (let i = 0; i < imageUrls.length; i++) {
    const task = await submitVideoTask(imageUrls[i], prompts[i]);
    tasks.push({ id: task.id, scene: i, status: 'processing' });
    await sleep(1000); // Stagger submissions
  }

  // Step 2: Poll for completion
  const completed = [];
  while (completed.length < tasks.length) {
    for (const task of tasks) {
      if (task.status === 'processing') {
        const status = await checkTaskStatus(task.id);
        if (status.state === 'completed') {
          task.status = 'completed';
          task.videoUrl = status.output_url;
          completed.push(task);
          console.log(`Scene ${task.scene} complete (${completed.length}/${tasks.length})`);
        } else if (status.state === 'failed') {
          task.status = 'failed';
          console.error(`Scene ${task.scene} failed: ${status.error}`);
          // Resubmit failed task
          const retry = await submitVideoTask(imageUrls[task.scene], prompts[task.scene]);
          task.id = retry.id;
          task.status = 'processing';
        }
      }
    }
    await sleep(10000); // Poll every 10 seconds
  }
  return completed;
};

class RateLimiter {
  constructor(maxRequests, windowMs) {
    this.maxRequests = maxRequests;
    this.windowMs = windowMs;
    this.requests = [];
  }

  async waitForSlot() {
    const now = Date.now();
    // Remove expired timestamps
    this.requests = this.requests.filter(t => now - t < this.windowMs);
    if (this.requests.length >= this.maxRequests) {
      const oldestRequest = this.requests[0];
      const waitTime = this.windowMs - (now - oldestRequest) + 100;
      console.log(`Rate limit reached. Waiting ${waitTime}ms...`);
      await sleep(waitTime);
    }
    this.requests.push(Date.now());
  }
}

// Usage: Max 7 DALL-E requests per 60 seconds
const dalleRateLimiter = new RateLimiter(7, 60000);

for (const prompt of imagePrompts) {
  await dalleRateLimiter.waitForSlot();
  const image = await generateImage(prompt);
  results.push(image);
}

// Step 1: Create a JSONL batch file
const batchRequests = topics.map((topic, i) => ({
  custom_id: `script-${i}`,
  method: 'POST',
  url: '/v1/chat/completions',
  body: {
    model: 'gpt-4',
    messages: [
      { role: 'system', content: 'Write a 60-second video script...' },
      { role: 'user', content: `Topic: ${topic}` }
    ]
  }
}));

// Step 2: Upload batch file
const file = await openai.files.create({
  file: createBatchFile(batchRequests),
  purpose: 'batch'
});

// Step 3: Create batch job (50% cheaper than real-time)
const batch = await openai.batches.create({
  input_file_id: file.id,
  endpoint: '/v1/chat/completions',
  completion_window: '24h'
});

// Step 4: Poll for results
// Results are available within 24 hours at half the cost

const qualityCheck = async (asset, type) => {
  const checks = {
    image: async (img) => {
      const metadata = await sharp(img).metadata();
      return {
        passed: metadata.width >= 1792 && metadata.height >= 1024,
        reason: metadata.width < 1792 ? 'Resolution too low' : 'OK',
        dimensions: `${metadata.width}x${metadata.height}`
      };
    },
    video: async (vid) => {
      const probe = await ffprobe(vid);
      const duration = parseFloat(probe.streams[0].duration);
      return {
        passed: duration >= 4.5 && duration <= 10.5,
        reason: duration < 4.5 ? 'Too short' : duration > 10.5 ? 'Too long' : 'OK',
        duration: `${duration}s`
      };
    },
    audio: async (aud) => {
      const probe = await ffprobe(aud);
      const duration = parseFloat(probe.streams[0].duration);
      const bitrate = parseInt(probe.streams[0].bit_rate);
      return {
        passed: bitrate >= 128000,
        reason: bitrate < 128000 ? 'Bitrate too low' : 'OK',
        duration: `${duration}s`
      };
    }
  };
  return checks[type](asset);
};