AI platform workflow with draggable components.
- 🚀 UI: simple to use, yet powerful
- 📐 DAG graph scheduling: Draggable-ai-workflow supports DAG workflow execution
- 💡 Parameterization: stage (unit of execution) can be parameterized to maximize configuration reuse
- 🛠 External integration: external systems like docker registry, Ali Cloud can be integrated with
- 🖥 Multi-cluster: workflow can be executed in different clusters
- 🙂 Multi-tenancy: resource manifests and workflow executions are grouped and isolated per tenant
- ... and many more
Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.
The page will reload if you make edits.
You will also see any lint errors in the console.
Launches the test runner in the interactive watch mode.
See the section about running tests for more information.
Builds the app for production to the build folder.
It correctly bundles React in production mode and optimizes the build for the best performance.
The build is minified and the filenames include the hashes.
Your app is ready to be deployed!
See the section about deployment for more information.
- Slack: Join Our Community for discussions, posting questions and contributions. If you are not yet a member of ai-workflow, you may sign up here.
If you are interested in contributing to draggable-ai-workflow, please checkout CONTRIBUTING.md. We welcome any code or non-code contribution!
Draggable-ai-workflow is licensed under the MIT License. See LICENSE for the full license text.