界面已本地化;技能介绍与说明文档按所选语言由 AI 自动翻译,代码、命令、路径和专业术语保留原文,以原作者文档为准。
探索技能
效率与协作 · SKILL.md

klingai-async-workflows

klingai-async-workflows

【效率与协作】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'.

独立 GitHub 快照 · 自动分类 · 以原作者文档为准

技能说明

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

我的收藏