使用 Hatchet 运行持久化代理任务和事件驱动的工作流

Use Hatchet to queue, retry, pause, resume, observe, and scale long-running agent tasks and background workflows.

Prerequisites

Hatchet CLI, Docker for local setup, Hatchet workers, and application code in Python, TypeScript, Go, Ruby, or another supported runtime

Installation

Requirements and caveats from upstream:
- Hatchet is a platform for orchestrating background tasks, AI agents, and durable workflows at scale. It supports applications written in Python, TypeScript, Go and Ruby, and can be used as a service through [Hatchet C...
- To run Hatchet locally, the fastest path for setup is to install the Hatchet CLI (on MacOS, Linux or WSL) - note that this requires Docker installed locally to work:
- When to use Hatchet: when you'd like to use a DAG-based framework, write your own integrations and functions, and require higher throughput (>100/s)

Basic usage or getting-started notes:
- <a href ="https://hatchet.run?utm_source=github&utm_campaign=readme">
- [![Go Referenc...
-

• Source: https://github.com/1991513ccie-png/skills
• Extracted from upstream docs: https://raw.githubusercontent.com/hatchet-dev/hatchet/HEAD/README.md

Documentation

• https://docs.hatchet.run