Klingai Batch Processing

Overview

This skill teaches efficient batch processing patterns for generating multiple videos, including parallel submission, progress tracking, rate limit management, and result collection.

Prerequisites

• Kling AI API key with sufficient credits
• Python 3.8+ with asyncio support
• Understanding of async/await patterns

Instructions

Follow these steps for batch processing:

1. Prepare Batch: Collect all prompts and parameters
2. Rate Limit Planning: Calculate submission pace
3. Parallel Submission: Submit jobs within limits
4. Track Progress: Monitor all jobs simultaneously
5. Collect Results: Gather outputs and handle failures

Output

Successful execution produces:

• Parallel job submission within rate limits
• Real-time progress tracking
• Collected results with success/failure status
• Performance metrics (duration, throughput)

Error Handling

See {baseDir}/references/errors.md for comprehensive error handling.

Examples

See {baseDir}/references/examples.md for detailed examples.

Resources

• Kling AI Batch API
• Python asyncio
• aiohttp Documentation