Deploying an AI search application through Vespa Cloud Services is divided into the following steps:
- Register for an account: Access console.vespa-cloud.com Complete the registration.
- Creating Applications: Create a new application in the console, selecting the appropriate geographic area and node configuration (e.g., adjusting the number of nodes based on the amount of data).
- Upload Configuration: Prepare data model definition files (e.g. Schema) and search ranking configurations (Ranking) to be uploaded via the platform.
- Deployment and Testing: After the system has automated the deployment, send a query request through the Vespa API, for example:
{ "yql": "select * from sources * where userQuery()" }
caveat: Cloud services are suitable for quick validation and small to medium sized projects that need to monitor quotas to avoid overruns. For complex requirements (e.g., customized ranking logic), it can be combined with local development to extend the functionality.
Compared to local deployment, cloud services eliminate the cost of environment configuration and cluster maintenance, which is suitable for teams that lack operation and maintenance resources.
This answer comes from the articleVespa.ai: an open source platform for building efficient AI search and recommendation systemsThe
May not be reproduced without permission:AI productivity tools " How to quickly deploy an AI search app using Vespa.ai's cloud services?
