https://github.com/zenml-io/zenml-dashboard
The repository that contains all source code for the ZenML UI.
https://github.com/zenml-io/zenml-dashboard
Last synced: 6 months ago
JSON representation
The repository that contains all source code for the ZenML UI.
- Host: GitHub
- URL: https://github.com/zenml-io/zenml-dashboard
- Owner: zenml-io
- Created: 2022-08-21T08:22:47.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-12-04T08:39:49.000Z (6 months ago)
- Last Synced: 2024-12-16T02:39:48.662Z (6 months ago)
- Language: TypeScript
- Size: 11.9 MB
- Stars: 44
- Watchers: 6
- Forks: 10
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE-OF-CONDUCT.md
Awesome Lists containing this project
README
Open-source companion dashboard for
ZenML.
Build portable, production-ready MLOps pipelines.
Features
·
Roadmap
·
Report Bug
·
Vote New Features
·
Read Blog
·
Meet the Team
---
# ⚡ Getting Started
## 🔋 Local Installation
To get started with the ZenML Dashboard, follow these steps:
1. **Install Node.js (v20):**
- Ensure you have Node.js installed. You can either install version 18 directly or use [nvm (Node Version Manager)](https://github.com/nvm-sh/nvm) with the following commands:
```bash
nvm install 20
nvm use 20
```
2. **Install Pnpm:**
- The project uses Pnpm as the package manager. Install it with:
```bash
npm install -g pnpm
```
3. **Install Dependencies:**
- Navigate to the project directory and install dependencies:
```bash
pnpm install
```
4. **Set Environment Variable:**
- Configure the environment variable `VITE_API_BASE_URL` by replacing `` with your ZenML Server deployment URL. Example:
```bash
export VITE_API_BASE_URL="https://your-zenml-server-url/api/v1"
```
> [!IMPORTANT]
> The frontend and the server-url needs to be on the same domain, e.g. `localhost` for local development
> [!NOTE]
> For local development you **don't** need to set `VITE_FEATURE_OS_KEY`
> You can set the `VITE_FRONTEND_VERSION` to a version number, e.g `v0.17.0`. This value is used to read the UI Version from the environment
5. **Run Development Server:**
- For development, run the server with:
```bash
pnpm dev
```
- Alternatively, build the project for production with:
```bash
pnpm build
```
6. **Using Docker (Optional):**
- ZenML provides Docker images for the server and dashboard. Run the following command to serve both:
```bash
docker run -it -d -p 8080:8080 --name zenml zenmldocker/zenml-server
```
- Access the dashboard at `http://localhost:8080`
For detailed deployment instructions and additional options, refer to the [deployment guide](https://docs.zenml.io/user-guide/production-guide/deploying-zenml).
Now you're ready to explore and visualize your ML pipelines, stacks, and artifacts with the ZenML Dashboard!
# 🤝 ZenML Dashboard Integration
The ZenML Dashboard is a Typescript React-based application designed to seamlessly integrate with the main [ZenML Python package](https://github.com/zenml-io/zenml). It serves as a unified platform for managing and visualizing your ML pipelines, stacks, and artifacts in one centralized location.
## Integration Overview
The ZenML Dashboard is intricately connected with the ZenML Server as its backend and is not intended for standalone use. Here's a brief overview of how it fits into the ZenML ecosystem:
- **Sister Repository:**
- The dashboard resides in this repository, acting as a sister repository to the main [ZenML Python package repo](https://github.com/zenml-io/zenml).
- **Bundled Build Files:**
- The dashboard build files are bundled into the [ZenML PyPi package](https://pypi.org/workspace/zenml/) and are included with each version of the ZenML Python package. These build files, generated by `yarn build`, correspond to specific versions of the dashboard.
- **Local Deployment:**
- Serve the static build files locally using the ZenML Python package:
```bash
zenml up
```
This creates a local daemon that serves the files in a [FastAPI](https://github.com/tiangolo/fastapi) server.
# 🏄 User Experience
## 🔐 Log In
Logging into the ZenML Dashboard is a simple process. Navigate to the login page and enter your credentials.
## 🗂 Pipelines, Stacks, Components and other resources
Explore your machine learning artifacts effortlessly. The dashboard offers a structured view of your pipelines, stacks, components, etc... making it easy to manage and visualize your workflows.
This combination of a user-friendly interface and visualizations enhances your experience, helping you navigate and understand your machine learning processes efficiently.
# 🙌 Contributing
We would love to develop ZenML together with our community! The best way to get
started is to select any issue from the [`good-first-issue`
label](https://github.com/zenml-io/zenml-dashboard/labels/good%20first%20issue).
If you would like to contribute, please review our [Contributing
Guide](CONTRIBUTING.md) for all relevant details.
# 🆘 Getting Help
Need a helping hand? We've got you covered! Getting assistance with ZenML is quick and easy.
1. **Join our Slack Community:**
- Our lively Slack community is buzzing with friendly faces and helpful discussions. Drop by, ask questions, and connect with fellow enthusiasts. [Get your invite](https://zenml.io/slack/).
2. **Open an Issue:**
- Have a specific problem or found a bug? Open an issue on our [GitHub repo](https://github.com/zenml-io/zenml-dashboard/issues/new/choose). Our team and community members regularly monitor and respond.
3. **Check the Documentation:**
- Explore our comprehensive [documentation](https://docs.zenml.io/) for in-depth guides, tutorials, and troubleshooting tips. It's a treasure trove of knowledge to empower your ZenML journey.
# 📜 License
ZenML Dashboard is distributed under the terms of the Apache License Version 2.0.
A complete version of the license is available in the [LICENSE](LICENSE) file in
this repository. Any contribution made to this workspace will be licensed under
the Apache License Version 2.0.
