Batch Processing: Handle Thousands of LLM Requests Efficiently

When to Batch

Batch processing is ideal for non-time-sensitive tasks like document analysis, bulk translation, and data enrichment.

Implementation Pattern

async function batchProcess(items: string[]) {
  const batchSize = 50;
  const results = [];
  
  for (let i = 0; i < items.length; i += batchSize) {
    const batch = items.slice(i, i + batchSize);
    const batchResults = await Promise.all(
      batch.map(item => callLLM(item))
    );
    results.push(...batchResults);
    await delay(1000); // Rate limit respect
  }
  return results;
}

Queue-Based Architecture

Use message queues (Redis, RabbitMQ) for reliable batch processing with retry logic and dead-letter queues.

Cost Optimization

Process batches during off-peak hours (2-6 AM UTC) for potential rate limit relief and reduced contention.