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'.
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill klingai-batch-processing63
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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.
Resources
- Commit
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- Last updated
- Created
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