klingai-batch-processing

# 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](https://docs.klingai.com/batch)
- [Python asyncio](https://docs.python.org/3/library/asyncio.html)
- [aiohttp Documentation](https://docs.aiohttp.org/)