If you wish to test the frontend only, you can build and run the frontend docker image, you can run the following command from the project root directory:
docker build . --target=frontend -t eas-kb-demo/frontend
docker run -p5000:5000 --rm --env-file=eas-kb-demo-frontend/.env eas-kb-demo/frontend
You can now use the frontend from your browser at http://host.docker.internal:5000.
Note:
- The docker build is a snapshot version of the production build to be deployed.
- Data from an ESS App Search instance
- If you want to develop the frontend, read the development documentation bellow.
If you wish to test the full stack build locally, you have to boot all the required services (Elasticsearch, App Search) using the docker-compose.yml
config with the project.
docker-compose up -d
It could take few minutes, for the stack to be fully booted. Once finished, you should be able to access:
- App Search admin at http://host.docker.internal:3002 using
app_search
/password
credentials - The frontend at http://host.docker.internal:5000
Note:
- All data are automatically imported when starting the stack. It can take few minutes before the result start to appear in the frontend.
- You can tune the engine relevance, curations, and synonyms by using the
helpdesk
meta engine in App Search. - The docker-compose stack is not intended to develop but to test built images. Images need to be refreshed everytime a change is made to the code using
docker-compose build
.
If something goes wrong with the import (use docker-compose logs -f dataimport
to view logs), you can restart it with:
docker-compose run dataimport start-dataimport.sh
To reset the whole stack (all data will be lost), use:
docker-compose down
The project can be installed by running:
yarn install
All sources of the frontend are located into the eas-kb-demo-frontend
workspace of the main yarn project.
By default, the frontend is configured to use the production App Search instance deployed in Elastic Cloud. Because frontend is a R/O application it should not be an issue.
To start the frontend, you can use:
yarn start
To run cypress tests for the frontend, you can use:
yarn cypress run
When working on the import, you should use your own version of App Search during the development.
The easiest way to get the stack up and running is to use the docker-compose
file bundled with this demo:
docker-compose up -d
After the stack will have finished to start, you can then access to App Search through your browser at http://localhost:3002 with the following credentials:
- login:
app_search
- password:
password
Notes :
- This demo uses meta engine which are available only when using a Platinum license.
You have to start a new trial for your App Search instance using the following command:
docker-compose exec elasticsearch curl -XPOST -uelastic:elasticpassword "localhost:9200/_license/start_trial?acknowledge=true"
docker-compose restart app-search
- When using Docker for Mac, please make sure you have at least 4GiB of memory allocated to Docker (
Preferences > Advanced
).
Out of memory errors can cause ElasticSearch or App Search container to be killed (docker logs --tail
can help to detect it).
The demo uses two different data sources:
- data scrapped from the Elastic documentation (
dataimport/data/data/elastic-co-docs.json
) - data scrapped from the Elastic discussion forum (
dataimport/data/data/elastic-co-discuss.json
)
You can import theses data into App Search by running:
yarn dataimport
Notes:
- The script will create one search engine in App Search for each dataset.
- The script will create one meta engine
helpdesk
that will be used to query all the dataset. If needed, relevance tunning should be done in the meta engine. - You will need to information during the setup:
- App Search API base URL: default is set to
http://localhost:3002/api/as/v1/
(should be fine) - App Search API private key: you can find it into the credentials section of the App Search dashboard (http://localhost:3002/as#/credentials)
- App Search API base URL: default is set to