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# Streamlit Forecasting Dashboard App: | ||
# Streamlit Forecasting Dashboard App: | ||
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we need here to create multi-page application that holds performance monitoring service of the model, and forecasting service that shows the forecasting, and actual temperature daily. | ||
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using [streamlit](https://docs.streamlit.io/get-started/tutorials/create-a-multipage-app), and [ploomber-cloud](https://ploomber.io/), we created multi page streamlit application, and deploy it easly. | ||
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to create multi page application, create all secondary pages in sub directory called `pages/`, and the main page must be named `app.py` to follow ploomber cloud instructions, like the following | ||
```shell | ||
# application file structure | ||
. | ||
|-- README.md | ||
|-- app.py | ||
|-- pages | ||
| |-- monitoring_service.py | ||
| `-- weather_forecasting_service.py | ||
|-- ploomber-cloud.json | ||
|-- requirements.txt | ||
`-- serve | ||
|-- monitoring.py | ||
`-- weather_forecasting.py | ||
``` | ||
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to deploy the application: | ||
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- create ploomber cloud account, and create API key. | ||
- first set API key using | ||
```shell | ||
ploomber-cloud key <API-key> | ||
``` | ||
- intialize it | ||
```shell | ||
ploomber-cloud init | ||
``` | ||
- you will be asked to choose project type | ||
- to deploy your application | ||
```shell | ||
ploomber-cloud deploy | ||
``` | ||
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to trigger, and refresh the application use Github actions [refresh-dashboard](../.github/workflows/refresh_dashboard.yml) |