You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
To get started with the ZenML Dashboard, follow these steps:
80
42
81
-
First, there is a pre-requisite to use [`node`](https://www.npmjs.com/) version 14.20.0 exactly. One can do this by installing the [`nvm`](https://github.com/nvm-sh/nvm) utility and then doing
43
+
1.**Install Node.js (v18):**
44
+
- 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:
82
45
83
-
```
84
-
nvm install 18
85
-
nvm use 18
86
-
```
46
+
```bash
47
+
nvm install 18
48
+
nvm use 18
49
+
```
87
50
88
-
Users also need to have [`yarn`](https://yarnpkg.com/) installed.
51
+
2. **Install Yarn:**
52
+
- The project uses Yarn as the package manager. Install it with:
89
53
90
-
Then you can run it by doing:
54
+
```bash
55
+
npm install -g yarn
56
+
```
91
57
92
-
```
93
-
yarn install
94
-
yarn start
95
-
```
58
+
3. **Install Dependencies:**
59
+
- Navigate to the project directory and install dependencies:
96
60
97
-
To build it:
61
+
```bash
62
+
yarn install
63
+
```
98
64
99
-
```
100
-
yarn build
101
-
```
65
+
4. **Set Environment Variable:**
66
+
- Configure the environment variable `REACT_APP_BASE_API_URL` by replacing `<YOUR_ZENML_SERVER_DEPLOYMENT_URL>` with your ZenML Server deployment URL. Example:
To learn how to get the `YOUR_ZENML_SERVER_DEPOLOYMENT_URL`, read the [deployment guide](https://docs.zenml.io/user-guide/starter-guide/switch-to-production).
75
+
```bash
76
+
yarn start
77
+
```
110
78
111
-
Lastly, if you would like to use Docker, then the ZenML team provides [DockerHub] images to serve the ZenML Server and Dashboard in one image:
79
+
- Alternatively, build the project for production with:
112
80
113
-
```shell
114
-
docker run -it -d -p 8080:80 zenmldocker/zenml-server
115
-
```
81
+
```bash
82
+
yarn build
83
+
```
116
84
117
-
Which will serve the dashboard with the server at `http://localhost:8080`, with username `default` and an empty password.
85
+
6. **Using Docker (Optional):**
86
+
- ZenML provides Docker images for the server and dashboard. Run the following command to serve both:
118
87
119
-
## 👨👦 Relationship with ZenML
88
+
```bash
89
+
docker run -it -d -p 8080:80 zenmldocker/zenml-server
90
+
```
120
91
121
-
The ZenML Dashboard is a Javascript React-based application that lives inside this repository, which is a sister repository of the main [ZenML Python package repo](https://github.com/zenml-io/zenml).
92
+
- Access the dashboard at `http://localhost:8080` with the username `default` and an empty password.
122
93
123
-
> **Note** - The ZenML Dashboard is meant to be used with the ZenML Server as a backend and cannot be used standalone.
94
+
For detailed deployment instructions and additional options, refer to the [deployment guide](https://docs.zenml.io/user-guide/starter-guide/switch-to-production).
124
95
125
-
The dashboard build files come bundled into the [ZenML PyPi package](https://pypi.org/workspace/zenml/) and can be [served locally](https://docs.zenml.io/user-guide/starter-guide#explore-the-dashboard) and/or [deployed on the cloud](https://docs.zenml.io) through the main ZenML python package.
96
+
Now you're ready to explore and visualize your ML pipelines, stacks, and artifacts with theZenML Dashboard!
126
97
127
-
Basically, each ZenML `Python` package comes with the build files (generated by `yarn build`) of a certain version of this dashboard (all build files of the dashboard can be seen in the [releases](https://github.com/zenml-io/zenml-dashboard/releases) section of this GitHub repo). Therefore, each ZenML PyPi package has bundled in it a corresponding version of this dashboard.
128
98
129
-
With the `Python` package, you can then serve these static build files by doing:
99
+
# 🤝 ZenML Dashboard Integration
130
100
131
-
```
132
-
zenml up
133
-
```
101
+
The ZenML Dashboard is a Javascript 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.
102
+
103
+
## Integration Overview
134
104
135
-
105
+
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:
106
+
107
+
- **Sister Repository:**
108
+
- The dashboard resides in this repository, acting as a sister repository to the main [ZenML Python package repo](https://github.com/zenml-io/zenml).
109
+
110
+
- **Bundled Build Files:**
111
+
- 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.
112
+
113
+
- **Local Deployment:**
114
+
- Serve the static build files locally using the ZenML Python package:
115
+
116
+
```bash
117
+
zenml up
118
+
```
119
+
120
+
This creates a local daemon that serves the files in a [FastAPI](https://github.com/tiangolo/fastapi) server.
136
121
137
-
Which creates a local daemon that serves the files in a [FastAPI](https://github.com/tiangolo/fastapi) server!
138
122
139
123
## 🪐 Deploying the dashboard
140
124
@@ -154,15 +138,18 @@ Just don't forget to set the `REACT_APP_BASE_API_URL` environment variable!
154
138
155
139
## 🔐 Log In
156
140
157
-
141
+
Logging into the ZenML Dashboard is a simple process. Navigate to the login page and enter your credentials.
158
142
159
143
## 🏠 Home Page
160
144
161
-
145
+
Once logged in, you'll be directed to the dashboard's home page. This page provides an overview of your projects, pipelines, and recent activities.
146
+
147
+
## 🗂 Pipelines, Stacks, Components and other resources
162
148
163
-
## 🗂 Pipelines, Stacks and Components
149
+
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.
150
+
151
+
This combination of a user-friendly interface and visualizations enhances your experience, helping you navigate and understand your machine learning processes efficiently.
164
152
165
-
166
153
167
154
# 🙌 Contributing
168
155
@@ -175,22 +162,31 @@ Guide](CONTRIBUTING.md) for all relevant details.
175
162
176
163
# 👩👩👧👦 Meet the Team
177
164
165
+
Get to know the faces behind ZenML. Our dedicated team is passionate about creating tools that empower your machine learning journey.
166
+
178
167
179
168
180
-
Every week, the ZenML [core team](https://zenml.io/company#CompanyTeam) will pop in for 30 minutes to interact directly with the community.
181
-
Sometimes, we'll be presenting a feature; other times, we'll take questions and have fun.
169
+
Every week, the ZenML [core team](https://zenml.io/company#CompanyTeam) spends 30 minutes interacting directly with the community. This time may involve feature presentations, Q&A sessions, or just casual discussions.
182
170
183
171
[Register now](https://zenml.io/meet) for the ZenML Meet the Community session. It's free and open to everyone.
184
172
185
-
Or subscribe to our [public events calendar](https://calendar.google.com/calendar/u/0/r?cid=Y19iaDJ0Zm44ZzdodXBlbnBzaWplY3UwMmNjZ0Bncm91cC5jYWxlbmRhci5nb29nbGUuY29t) to get notified
186
-
before every community gathering.
173
+
You can also subscribe to our [public events calendar](https://calendar.google.com/calendar/u/0/r?cid=Y19iaDJ0Zm44ZzdodXBlbnBzaWplY3UwMmNjZ0Bncm91cC5jYWxlbmRhci5nb29nbGUuY29t) to stay informed about upcoming community gatherings.
174
+
175
+
Join us and become part of the ZenML community!
176
+
187
177
188
178
# 🆘 Getting Help
189
179
190
-
By far the easiest and fastest way to get a response is to:
180
+
Need a helping hand? We've got you covered! Getting assistance with ZenML is quick and easy.
181
+
182
+
1. **Join our Slack Community:**
183
+
- 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-invite/).
184
+
185
+
2. **Open an Issue:**
186
+
- 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.
191
187
192
-
1. Ask your questions in [our Slack group](https://zenml.io/slack-invite/).
193
-
2.[Open an issue](https://github.com/zenml-io/zenml-dashboard/issues/new/choose) on our GitHub repo.
188
+
3. **Check the Documentation:**
189
+
- 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.
0 commit comments