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 ${CLAUDE_SKILL_DIR}/references/errors.md for comprehensive error handling.

Examples

See ${CLAUDE_SKILL_DIR}/references/examples.md for detailed examples.

Resources

• Kling AI Batch API

• Python asyncio

• aiohttp Documentation