klingai-batch-processing

Process multiple video generation requests efficiently with Kling AI. Use when generating multiple videos or building content pipelines. Trigger with phrases like 'klingai batch', 'kling ai bulk', 'multiple videos klingai', 'klingai parallel generation'.

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:

Prepare Batch: Collect all prompts and parameters
Rate Limit Planning: Calculate submission pace
Parallel Submission: Submit jobs within limits
Track Progress: Monitor all jobs simultaneously
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.