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생산성 및 협업 · SKILL.md

klingai-async-workflows

klingai-async-workflows

Build asynchronous video generation workflows with Kling AI. Use when integrating video generation into larger systems or pipelines. Trigger with phrases like 'klingai async', 'kling ai workflow', 'klingai pipeline', 'async video generation'.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: klingai-async-workflows description: | Build asynchronous video generation workflows with Kling AI. Use when integrating video generation into larger systems or pipelines. Trigger with phrases like 'klingai async', 'kling ai workflow', 'klingai pipeline', 'async video generation'. allowed-tools: Read, Write, Edit, Grep version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io

Klingai Async Workflows

Overview

This skill demonstrates building asynchronous workflows for video generation, including job queues, state machines, event-driven processing, and integration with workflow orchestration systems.

Prerequisites

  • Kling AI API key configured
  • Python 3.8+ or Node.js 18+
  • Message queue (Redis, RabbitMQ) or workflow engine

Instructions

Follow these steps to build async workflows:

  1. Design Workflow: Map out the video generation pipeline
  2. Implement Queue: Set up job queue for async processing
  3. Create Workers: Build workers to process jobs
  4. Handle States: Manage job state transitions
  5. Add Monitoring: Track workflow progress

Output

Successful execution produces:

  • Validated and queued workflow jobs
  • State machine driven processing
  • Complete audit trail of transitions
  • Reliable job completion or failure handling

Error Handling

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

Examples

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

Resources

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