This is a sample website written in Typescript utilizing the Kontent.ai Delivery API to retrieve content. You can register your account for free at https://app.kontent.ai.
- Install the latest version of NodeJS and npm. You can download both at https://nodejs.org/en/download/.
- Clone the sample application repository.
- Navigate to the root folder of the application in the command line.
- Type
npm installto install required npm packages. - Type
npm run devto start a development server. - The application opens in your browser at http://localhost:5173.
On the first run of the app, you'll be presented with a configuration page. It will allow you to connect the app to your Kontent.ai sample project or create a new one. You'll also be able to start a trial and convert to a developer plan when the trial expires.
If you want to open the configuration page after the project is already connected to the app. Just open the URL http://localhost:5173/Admin/Configuration.
Alternatively, you can connect your project manually as per the chapter below.
If you want to change the source Kontent.ai project, follow these steps:
- In Kontent.ai, choose Environment settings from the app menu.
- Under the General settings, copy Environment ID.
- Create and open a
.env.localfile in the sample application folder. - On the first line, add your Environment ID constant using the format
VITE_VUE_APP_ENVIRONMENT_ID=00000000-0000-0000-0000-000000000000. - Save the file.
Now, when you run the application, it will retrieve the content from your sample project. This setup has a higher priority than setting your sample project via the Configuration page.
To preview unpublished content in the sample application, follow these steps:
- In Kontent.ai, choose Project settings from the app menu.
- Under Production environment settings, choose API keys.
- Copy your Environment ID and Preview API key.
- Create and open a
.env.localfile in the sample application folder. - On the first line, add your Environment ID constant using the format
VITE_VUE_APP_ENVIRONMENT_ID=00000000-0000-0000-0000-000000000000. - On the next line, add your Preview API key using the format
VUE_APP_PREVIEW_API_KEY=00000000-0000-0000-0000-000000000000. - Save the file.
Now, when you now run the application, you will see all project content including the unpublished version of content items.
- Navigate to https://app.kontent.ai in your browser.
- Sign in with your credentials.
- Manage content in the content administration interface of your sample project.
You can learn more about content editing at Kontent.ai Learn.
You can retrieve content either through the Kontent.ai Delivery SDKs or the Kontent.ai Delivery API:
- For published content, use
https://deliver.kontent.ai/ENVIRONMENT_ID/items. - For unpublished content, use
https://preview-deliver.kontent.ai/ENVIRONMENT_ID/items.
For more info about the API, see the API reference.
You can find the Delivery and other SDKs at https://github.com/kontent-ai.
This sample wants to showcase loading content from Kontent.ai as well as loading some part of the site from static JSON resources.
Basically, the content that you can't find in the
Localizationfolder is loaded from Kontent.ai.
- The data provided from
Localizationare using thevue-i18nplugin, so every call in components usingt('KEYWORD')in components is loading data from these JSONs as "Banner" section" (component here)
There are two types of model mapping in this application:
Content type definitions are generated from content types via Kontent.ai model generator tool. All types can be found in src/Models folder. The _project.ts contains information about the project structure such as project languages as well as other structure information like codenames about content types.
Some models displayed in views might require an adjustment from content types. For example, the content type Cafe contains fields for city and street and we would like to have a model containing an address in the format city, street. You can find an example of such a view model in CafeModel.tsx located in the src/ViewModels folder. Converting Cafe into CafeModel can be done by the function located in src/Utilities/CafeListing.ts.
This solution fetches data using the Kontent.ai Delivery client. For more implementation detail on how to set up the client see src/Client.js. After your client is set up, you are able to deliver your content to your project. The following example showcases how to use a Kontent.ai delivery client to fetch data.
const fetchBrewer = () => {
var query = Client.items<Brewer>()
.type('brewer')
.equalsFilter('url_pattern', route.params.brewerSlug as string)
if(language) {
query.languageParameter(language)
}
query
.toPromise()
.then(response => {
// store data to the state variable of your component.
brewer.value = response.data.items[0]
}
}To deal with content that is not available in the current language, this project uses a method called language fallbacks. It will fetch the content in the language set as a fallback language in the Kontent.ai project and redirect the website to the URL with a prefix of the given language. However, it is possible to disable language fallbacks by adding a filter of system.language to your query. For more information about getting localized content check this link.
var query = Client.items<AboutUs>().type('about_us');
if (language) {
query
.languageParameter(language)
.equalsFilter('system.language', 'es-ES');
}For the not found resources, prefixed 404 pages are used for both languages. As the content on one page should be in one language, this approach might help you to optimize SEO. If language is not set in the URL the application uses the last used language, which is set in cookies.
You can use, for example, surge to deploy your app live. Check out the step-by-step guide on our blog.
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