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Adding Enterprise Search to WordPress with Viglet Turing

· 4 min read

Alexandre OliveiraCreator & Lead Developer, Viglet Turing

WordPress ships with a built-in search that runs a LIKE query against the posts table. It works for a handful of posts, but on a real content site it has no relevance ranking, no facets, no typo tolerance, no autocomplete, and it slows down as your database grows. Most teams reach for a SaaS layer (Algolia, ElasticPress + hosted Elasticsearch) and start paying per record and per query.

This guide shows the open-source alternative: indexing WordPress into Viglet Turing, an Apache-2.0 enterprise search platform you self-host, with faceted search, semantic navigation, and generative AI (RAG), and your content staying on your own infrastructure.

The connector is a WordPress plugin, not a Java service

The Adobe AEM connector is a Java plugin loaded into the Viglet Dumont process. The WordPress connector works differently: it is a PHP plugin you install directly inside WordPress. It talks to Turing over HTTP, so there is no separate connector JAR to run.

Diagram: The connector is a WordPress plugin, not a Java service

Indexing follows your edits, without making editors wait on Turing:

WordPress event What happens
Post/page published or updated Queued, then sent to Turing
Content trashed, deleted or unpublished Queued, then removed from the index

A save only queues the post. A worker (WP-Cron, or wp dumont queue run) sends the queue in batches and retries with backoff when Turing is unreachable, so an outage never blocks the editor or drops a change. For the first load, the Setup page (or wp dumont index) indexes everything already published.

Step 1: Run Turing

The fastest path is Docker:

docker pull ghcr.io/openviglet/turing-ce:latest
docker run -p 2700:2700 ghcr.io/openviglet/turing-ce:latest

Open http://localhost:2700/console, set the admin password on first run, and create a Semantic Navigation (SN) Site. This is the index your WordPress content will land in.

Step 2: Install the WordPress plugin

Download viglet-dumont-<version>.zip from the Dumont releases and upload it under Plugins → Add New → Upload Plugin (or install it with Composer or WP-CLI, see the reference). Then activate it.

Step 3: Connect to Turing

Open Viglet Dumont → Setup and enter the Turing URL (for example http://localhost:2700), an API token from the Turing console, and the SN site name. Save and test the connection checks the address, the network, that it is a Turing, the key and the SN site. If one fails, it says which. If the SN site does not exist yet, it offers to create it. Then Index everything now loads your published content.

On a container deploy, the same settings can come from environment variables (VIGLET_DUMONT_TURING_URL, VIGLET_DUMONT_TURING_SITE, VIGLET_DUMONT_TURING_API_KEY), so the site comes up configured and the key never lands in the database.

What gets indexed

Each post becomes one document: title, rendered text, abstract, URL, type, author, publication and modification dates, image, and its categories and tags.

The Fields page goes further. Per post type, it turns your custom taxonomies and custom fields into typed Turing fields (dates, numbers, booleans, multi-valued strings) and marks the ones to filter by as facets. Saving sends those fields to Turing, so facets need no console step, and the page shows what a real post sends. With nothing configured, every public custom taxonomy already becomes a facet.

Every document id starts with a site key (the site's address by default), and each document carries it as a facet. Several WordPress sites, or every blog of a multisite network, can publish into one SN site for a unified search, without overwriting each other.

Step 4: Query it

Your WordPress content is now searchable through the Turing API, via REST, GraphQL, or the SDK:

# Faceted search
curl "http://localhost:2700/api/sn/wp-search/search?q=tutorial&rows=10&_setlocale=en_US"

# Autocomplete
curl "http://localhost:2700/api/sn/wp-search/ac?q=tut&_setlocale=en_US"

You rarely need to, though. Turn on Replace WordPress search with Turing and your theme's own search page shows Turing's ranking, with the theme's header, footer and styles intact. Or drop the Turing search block on any page: it gives you suggestions as you type, "did you mean", facets and pages, built on Turing's JS SDK, which the plugin also exposes to your theme as a script module.

Step 5 (optional): Conversational answers (RAG)

Because Turing already holds your WordPress content, turning on RAG gives you grounded AI answers with citations over your own posts, with the LLM of your choice (OpenAI, Ollama, Anthropic, Gemini):

curl "http://localhost:2700/api/sn/wp-search/chat?q=How+do+I+reset+my+password"
  • Your content stays in your infrastructure: no per-record SaaS pricing, no data egress.
  • Taxonomies and custom fields → typed facets, provisioned for you, with a queue that keeps indexing in step with your edits through Turing outages.
  • Search + semantic + RAG in one platform under Apache 2.0.

Next steps

Viglet Turing is open-source (Apache 2.0) enterprise search with semantic navigation and generative AI. Self-host it, index WordPress, Adobe AEM, databases, file systems, and web content, and own your search stack end to end.