The project is in a healthy, maintained state
An easy-to-use ruby client for Meilisearch API. See https://github.com/meilisearch/meilisearch


>= 0.17.1, < 0.22.0
 Project Readme


Meilisearch Ruby

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⚡ The Meilisearch API client written for Ruby 💎

Meilisearch Ruby is the Meilisearch API client for Ruby developers.

Meilisearch is an open-source search engine. Learn more about Meilisearch.

Table of Contents

  • 📖 Documentation
  • ⚡ Supercharge your Meilisearch experience
  • 🔧 Installation
  • 🚀 Getting started
  • 🤖 Compatibility with Meilisearch
  • 💡 Learn more
  • ⚙️ Contributing

📖 Documentation

This readme contains all the documentation you need to start using this Meilisearch SDK.

For general information on how to use Meilisearch—such as our API reference, tutorials, guides, and in-depth articles—refer to our main documentation website.

⚡ Supercharge your Meilisearch experience

Say goodbye to server deployment and manual updates with Meilisearch Cloud. Get started with a 14-day free trial! No credit card required.

🔧 Installation

We officially support any version of Ruby that is still receiving at least security maintenance. You may, however, be fine with any Ruby version above 3.0. However, we cannot guarantee support if your version is no longer being maintained.

With gem in command line:

gem install meilisearch

In your Gemfile with bundler:

source 'https://rubygems.org'

gem 'meilisearch'

Run Meilisearch

There are many easy ways to download and run a Meilisearch instance.

For example, using the curl command in your Terminal:

# Install Meilisearch
curl -L https://install.meilisearch.com | sh

# Launch Meilisearch
./meilisearch --master-key=masterKey

NB: you can also download Meilisearch from Homebrew or APT or even run it using Docker.

🚀 Getting started

Add documents

require 'meilisearch'

client = MeiliSearch::Client.new('', 'masterKey')

# An index is where the documents are stored.
index = client.index('movies')

documents = [
  { id: 1, title: 'Carol', genres: ['Romance', 'Drama'] },
  { id: 2, title: 'Wonder Woman', genres: ['Action', 'Adventure'] },
  { id: 3, title: 'Life of Pi', genres: ['Adventure', 'Drama'] },
  { id: 4, title: 'Mad Max: Fury Road', genres: ['Adventure', 'Science Fiction'] },
  { id: 5, title: 'Moana', genres: ['Fantasy', 'Action']},
  { id: 6, title: 'Philadelphia', genres: ['Drama'] },
# If the index 'movies' does not exist, Meilisearch creates it when you first add the documents.
index.add_documents(documents) # => { "uid": 0 }

With the uid, you can check the status (enqueued, canceled, processing, succeeded or failed) of your documents addition using the task.

💡 To customize the Client, for example, increasing the default timeout, please check out this section of the Wiki.

Basic Search

# Meilisearch is typo-tolerant:
puts index.search('carlo')


  "hits" => [{
    "id" => 1,
    "title" => "Carol"
  "offset" => 0,
  "limit" => 20,
  "processingTimeMs" => 1,
  "query" => "carlo"

Custom search

All the supported options are described in the search parameters section of the documentation.

  attributes_to_highlight: ['*']

JSON output:

    "hits": [
            "id": 2,
            "title": "Wonder Woman",
            "_formatted": {
                "id": 2,
                "title": "<em>Wonder</em> Woman"
    "offset": 0,
    "limit": 20,
    "processingTimeMs": 0,
    "query": "wonder"

Custom Search With Filters

If you want to enable filtering, you must add your attributes to the filterableAttributes index setting.


You only need to perform this operation once.

Note that Meilisearch will rebuild your index whenever you update filterableAttributes. Depending on the size of your dataset, this might take time. You can track the process using the tasks).

Then, you can perform the search:

index.search('wonder', { filter: ['id > 1 AND genres = Action'] })

JSON output:

  "hits": [
      "id": 2,
      "title": "Wonder Woman",
      "genres": [
  "estimatedTotalHits": 1,
  "query": "wonder",
  "limit": 20,
  "offset": 0,
  "processingTimeMs": 0

Display ranking details at search

JSON output:

  "hits": [
      "id": 15359,
      "title": "Wonder Woman",
      "_rankingScoreDetails": {
        "words": {
          "order": 0,
          "matchingWords": 2,
          "maxMatchingWords": 2,
          "score": 1.0
        "typo": {
          "order": 1,
          "typoCount": 0,
          "maxTypoCount": 2,
          "score": 1.0
        "proximity": {
          "order": 2,
          "score": 1.0
        "attribute": {
          "order": 3,
          "attributeRankingOrderScore": 0.8181818181818182,
          "queryWordDistanceScore": 1.0,
          "score": 0.8181818181818182
        "exactness": {
          "order": 4,
          "matchType": "exactMatch",
          "score": 1.0

This feature is only available with Meilisearch v1.3 and newer (optional).

Custom Search With attributes on at search time

Customize attributes to search on at search time.

you can perform the search :

index.search('wonder', { attributes_to_search_on: ['genres'] })

JSON output:


This feature is only available with Meilisearch v1.3 and newer (optional).

🤖 Compatibility with Meilisearch

This package guarantees compatibility with version v1.x of Meilisearch, but some features may not be present. Please check the issues for more info.

💡 Learn more

The following sections in our main documentation website may interest you:

📖 Also, check out the Wiki of this repository to know what this SDK provides!

⚙️ Contributing

Any new contribution is more than welcome in this project!

If you want to know more about the development workflow or want to contribute, please visit our contributing guidelines for detailed instructions!

Meilisearch provides and maintains many SDKs and Integration tools like this one. We want to provide everyone with an amazing search experience for any kind of project. If you want to contribute, make suggestions, or just know what's going on right now, visit us in the integration-guides repository.