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Application: search-api-v2

API and synchronisation worker for general site search on GOV.UK


API and synchronisation worker for general site search on GOV.UK

This application powers the new site search for GOV.UK using Google Cloud Platform (GCP)‘s Vertex AI Search (“Discovery Engine”) product as its underlying search engine. It provides two core pieces of functionality:

  • An API that is “minimally compatible” with the existing search-api REST interface to the extent necessary to power the “site search” (/search/all) finder.
  • A synchonisation worker that receives content updates from the Publishing API message queue and updates the Discovery Engine dataset accordingly

Local development

The official way of running this application locally is through GOV.UK Docker, where a project is defined for it. Because this application is deeply integrated with a SaaS product, you will have to have access to a GCP Discovery Engine engine to be able to do anything more meaningful than running the test suite. govuk-docker will do this for you by configuring the DISCOVERY_ENGINE_SERVING_CONFIG and DISCOVERY_ENGINE_DATASTORE_BRANCH environment variables your in local set-up to point to integration.

You can run the application from within the govuk-docker repository directory as follows:

Building search-api-v2

make search-api-v2

Running search-api-v2

gcloud auth application-default login
govuk-docker up -d search-api-v2-app # or search-api-v2-lite if you just want to run tests

Design goals and search-api-v2 vs search-api

Our primary product goal was to improve the quality of search results for the majority of GOV.UK users.

The existing search powers a significant number of use cases within GOV.UK, including numerous user-facing “finder” pages handled by Finder Frontend (among them the /search/all finder that handles the main search page which we usually refer to as “site search”), but also acts as a very general “everything but the kitchen sink” API for retrieving content by a set of criteria.

We established that attempting to migrate all of these use cases with over a decade of accumulated logic and edge cases would distract us from our primary goal and be a poor fit for a next-generation search product anyway (the overwhelming majority of non-“site search” queries being trivial content retrieval filtered by certain attributes that could be handled by a relational database).

We therefore made a tactical decision to focus on “site search” only and find the minimal subset of the existing API contract that is necessary to render search results in this context, and update Finder Frontend to call our new application if and only if the user is using the general “site search” finder.

Nothing in this application precludes more use cases being migrated to it in the future, but for the time being, it is intentionally not a complete replacement for Search API (despite the “v2” name).

See Search API compatibility for more information about our compatibility design choices.

“Vertex” vs “Discovery Engine”

The marketing name of the search product we use (Google Vertex AI Search and Conversation) has undergone several changes while this application was first developed, and some concepts have different naming in the Google Cloud Platform UI compared to the actual underlying APIs themselves.

We have chosen to exclusively use the more stable API naming (Discovery Engine, engine instead of app, etc.) throughout the codebase and documentation to avoid having to rename things as the product reached general availability, but you may see the terms “Vertex” or “Vertex Search” as well as some other marketing terms used in some project artefacts.

  • finder-frontend: Displays results from this application’s API depending on the “finder” in use and some other conditions
  • search-api: The original Search API, a subset of which this application’s API replicates
  • search-v2-infrastructure: Provisions infrastructure for Discovery Engine including cloud resources and event ingestion for continuous training of the search engine
  • search-v2-evaluator: Internal tool to test and rate search results