Semantic Search

AI-powered semantic search for Strapi CMS using embedding models. Search your content by meaning, not just keywords.

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Strapi Semantic Search Plugin

AI-powered semantic search for Strapi CMS using embedding models. Search your content by meaning, not just keywords.

Quick start
Description
Configuration
API endpoints
Troubleshooting
Local development
Contributing
License

Quick start

To add semantic search to your local Strapi instance, simply install the npm package.

npm install strapi-semantic-search
# or
yarn add strapi-semantic-search

Once installed, navigate to the semantic search tab in the admin panel and configure the content to be serach.

For strapi cloud, we are working on getting this plugin into Strapi market, stay tuned.

Description

The main goal of this plugin is to allow users to easily setup and use semantic search with any embedding model that they want. The plugin provide the following features:

Semantic Search: Find content based on meaning using AI embeddings
Multi-Provider Support: Works with any OpenAI-compatible API
Auto-Generation: Automatically generate embeddings when content is created or updated
Multi-Content Type: Search across multiple content types simultaneously
Embedding Management: View statistics, regenerate, or delete embeddings from the UI
Note: Currently the plugin will only generate embeddings for content that is published.

Configuration

Head to the admin panel and use the UI to configure your embedding model connection details and the plugin settings. You can find the content type of the your content from the url, e.g. http://localhost:1337/admin/content-manager/collection-types/api::article.article. For more examples on configuration, check the screenshots folder.

Field Configuration

Each content type has the following configurable fields:

Setting	Purpose	Example
Searchable fields	Top-level fields the plugin reads to build embedding text.	`title, description, blocks`
Populate fields	Relations, components, dynamic zones, or media fields to load from the database. Scalar fields (strings, numbers, booleans, dates) are always included automatically and should not be listed here. Leave empty to populate all fields.	`blocks, author, coverImage`

Important: The populateFields setting only accepts relation, component, dynamic zone, and media field names. Scalar fields like title, description, slug, etc. are always returned by Strapi and do not need to be populated. Adding a scalar field to populateFields will cause a validation error. See Strapi's REST API for more details.

Similarity Scores

When searching you can configure the similarity score threshold which is a number 0-1 that indicates how relevant the content is to the query. Lower values return more results but may include less relevant content. In practice, we found that for searching in longer pieces of text 0.25 - 0.3 indicates that the article is relevant.

API Endpoints

All endpoints are available under /api/strapi-semantic-search/. You can optionally pass populate in the request body to control which relations are loaded on results—same format as Strapi's REST API: "*" (all), ["author", "cover"], or a deep object. See documentation for the full OpenAPI spec.

Search Single Content Type

POST /api/strapi-semantic-search/search
Content-Type: application/json

{
  "query": "digital transformation in banking",
  "contentType": "api::article.article",
  "limit": 10,
  "threshold": 0.3,
  "locale": "en",
  "populate": ["author"]
}

Search Multiple Content Types

POST /api/strapi-semantic-search/multi-search
Content-Type: application/json

{
  "query": "financial services consulting",
  "contentTypes": ["api::article.article", "api::page.page"],
  "limit": 10,
  "threshold": 0.3,
  "locale": "en"
  "populate": ["author"]
}

Troubleshooting

Check the console logs in your Strapi instance with the [Semantic Search] prefix. Common issues include

Misconfigured API settings
Searching for unpublished content
Embeddings have not been generated yet
Threshold is set too high

Local Development

For local plugin development, view this guide on how to link a local plugin to a local Strapi instance with yalc. Essentially

# In the plugin directory
npm install
npm run build
npm run watch:link

# In the Strapi instance
npm install openai
npx yalc add strapi-semantic-search && npx yalc link strapi-semantic-search && npx install
npm run develop

Contributing

Thank you for your interest in contributing to the semantic search plugin! This plugin is created and maintained by Synpulse. If you would like to contribute to the project, please create an issue and submit a pull request. Our maintainers will review your pull request as soon as possible.