base on Intelligent search made easy # Searchkick
:rocket: Intelligent search made easy
**Searchkick learns what your users are looking for.** As more people search, it gets smarter and the results get better. It’s friendly for developers - and magical for your users.
Searchkick handles:
- stemming - `tomatoes` matches `tomato`
- special characters - `jalapeno` matches `jalapeño`
- extra whitespace - `dishwasher` matches `dish washer`
- misspellings - `zuchini` matches `zucchini`
- custom synonyms - `pop` matches `soda`
Plus:
- query like SQL - no need to learn a new query language
- reindex without downtime
- easily personalize results for each user
- autocomplete
- “Did you mean” suggestions
- supports many languages
- works with Active Record and Mongoid
Check out [Searchjoy](https://github.com/ankane/searchjoy) for analytics and [Autosuggest](https://github.com/ankane/autosuggest) for query suggestions
:tangerine: Battle-tested at [Instacart](https://www.instacart.com/opensource)
[](https://github.com/ankane/searchkick/actions)
## Contents
- [Getting Started](#getting-started)
- [Querying](#querying)
- [Indexing](#indexing)
- [Intelligent Search](#intelligent-search)
- [Instant Search / Autocomplete](#instant-search--autocomplete)
- [Aggregations](#aggregations)
- [Testing](#testing)
- [Deployment](#deployment)
- [Performance](#performance)
- [Advanced Search](#advanced)
- [Reference](#reference)
- [Contributing](#contributing)
## Getting Started
Install [Elasticsearch](https://www.elastic.co/downloads/elasticsearch) or [OpenSearch](https://opensearch.org/downloads.html). For Homebrew, use:
```sh
brew install elastic/tap/elasticsearch-full
brew services start elasticsearch-full
# or
brew install opensearch
brew services start opensearch
```
Add these lines to your application’s Gemfile:
```ruby
gem "searchkick"
gem "elasticsearch" # select one
gem "opensearch-ruby" # select one
```
The latest version works with Elasticsearch 7 and 8 and OpenSearch 1 and 2. For Elasticsearch 6, use version 4.6.3 and [this readme](https://github.com/ankane/searchkick/blob/v4.6.3/README.md).
Add searchkick to models you want to search.
```ruby
class Product < ApplicationRecord
searchkick
end
```
Add data to the search index.
```ruby
Product.reindex
```
And to query, use:
```ruby
products = Product.search("apples")
products.each do |product|
puts product.name
end
```
Searchkick supports the complete [Elasticsearch Search API](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-search.html) and [OpenSearch Search API](https://opensearch.org/docs/latest/opensearch/rest-api/search/). As your search becomes more advanced, we recommend you use the [search server DSL](#advanced) for maximum flexibility.
## Querying
Query like SQL
```ruby
Product.search("apples", where: {in_stock: true}, limit: 10, offset: 50)
```
Search specific fields
```ruby
fields: [:name, :brand]
```
Where
```ruby
where: {
expires_at: {gt: Time.now}, # lt, gte, lte also available
orders_count: 1..10, # equivalent to {gte: 1, lte: 10}
aisle_id: [25, 30], # in
store_id: {not: 2}, # not
aisle_id: {not: [25, 30]}, # not in
user_ids: {all: [1, 3]}, # all elements in array
category: {like: "%frozen%"}, # like
category: {ilike: "%frozen%"}, # ilike
category: /frozen .+/, # regexp
category: {prefix: "frozen"}, # prefix
store_id: {exists: true}, # exists
_not: {store_id: 1}, # negate a condition
_or: [{in_stock: true}, {backordered: true}],
_and: [{in_stock: true}, {backordered: true}]
}
```
Order
```ruby
order: {_score: :desc} # most relevant first - default
```
[All of these sort options are supported](https://www.elastic.co/guide/en/elasticsearch/reference/current/sort-search-results.html)
Limit / offset
```ruby
limit: 20, offset: 40
```
Select
```ruby
select: [:name]
```
[These source filtering options are supported](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-fields.html#source-filtering)
### Results
Searches return a `Searchkick::Relation` object. This responds like an array to most methods.
```ruby
results = Product.search("milk")
results.size
results.any?
results.each { |result| ... }
```
By default, ids are fetched from the search server and records are fetched from your database. To fetch everything from the search server, use:
```ruby
Product.search("apples", load: false)
```
Get total results
```ruby
results.total_count
```
Get the time the search took (in milliseconds)
```ruby
results.took
```
Get the full response from the search server
```ruby
results.response
```
**Note:** By default, Elasticsearch and OpenSearch [limit paging](#deep-paging) to the first 10,000 results for performance. This applies to the total count as well.
### Boosting
Boost important fields
```ruby
fields: ["title^10", "description"]
```
Boost by the value of a field (field must be numeric)
```ruby
boost_by: [:orders_count] # give popular documents a little boost
boost_by: {orders_count: {factor: 10}} # default factor is 1
```
Boost matching documents
```ruby
boost_where: {user_id: 1}
boost_where: {user_id: {value: 1, factor: 100}} # default factor is 1000
boost_where: {user_id: [{value: 1, factor: 100}, {value: 2, factor: 200}]}
```
Boost by recency
```ruby
boost_by_recency: {created_at: {scale: "7d", decay: 0.5}}
```
You can also boost by:
- [Conversions](#intelligent-search)
- [Distance](#boost-by-distance)
### Get Everything
Use a `*` for the query.
```ruby
Product.search("*")
```
### Pagination
Plays nicely with kaminari and will_paginate.
```ruby
# controller
@products = Product.search("milk", page: params[:page], per_page: 20)
```
View with kaminari
```erb
<%= paginate @products %>
```
View with will_paginate
```erb
<%= will_paginate @products %>
```
### Partial Matches
By default, results must match all words in the query.
```ruby
Product.search("fresh honey") # fresh AND honey
```
To change this, use:
```ruby
Product.search("fresh honey", operator: "or") # fresh OR honey
```
By default, results must match the entire word - `back` will not match `backpack`. You can change this behavior with:
```ruby
class Product < ApplicationRecord
searchkick word_start: [:name]
end
```
And to search (after you reindex):
```ruby
Product.search("back", fields: [:name], match: :word_start)
```
Available options are:
Option | Matches | Example
--- | --- | ---
`:word` | entire word | `apple` matches `apple`
`:word_start` | start of word | `app` matches `apple`
`:word_middle` | any part of word | `ppl` matches `apple`
`:word_end` | end of word | `ple` matches `apple`
`:text_start` | start of text | `gre` matches `green apple`, `app` does not match
`:text_middle` | any part of text | `een app` matches `green apple`
`:text_end` | end of text | `ple` matches `green apple`, `een` does not match
The default is `:word`. The most matches will happen with `:word_middle`.
To specify different matching for different fields, use:
```ruby
Product.search(query, fields: [{name: :word_start}, {brand: :word_middle}])
```
### Exact Matches
To match a field exactly (case-sensitive), use:
```ruby
Product.search(query, fields: [{name: :exact}])
```
### Phrase Matches
To only match the exact order, use:
```ruby
Product.search("fresh honey", match: :phrase)
```
### Stemming and Language
Searchkick stems words by default for better matching. `apple` and `apples` both stem to `appl`, so searches for either term will have the same matches.
Searchkick defaults to English for stemming. To change this, use:
```ruby
class Product < ApplicationRecord
searchkick language: "german"
end
```
See the [list of languages](https://www.elastic.co/guide/en/elasticsearch/reference/current/analysis-stemmer-tokenfilter.html#analysis-stemmer-tokenfilter-configure-parms). A few languages require plugins:
- `chinese` - [analysis-ik plugin](https://github.com/medcl/elasticsearch-analysis-ik)
- `chinese2` - [analysis-smartcn plugin](https://www.elastic.co/guide/en/elasticsearch/plugins/current/analysis-smartcn.html)
- `japanese` - [analysis-kuromoji plugin](https://www.elastic.co/guide/en/elasticsearch/plugins/current/analysis-kuromoji.html)
- `korean` - [analysis-openkoreantext plugin](https://github.com/open-korean-text/elasticsearch-analysis-openkoreantext)
- `korean2` - [analysis-nori plugin](https://www.elastic.co/guide/en/elasticsearch/plugins/current/analysis-nori.html)
- `polish` - [analysis-stempel plugin](https://www.elastic.co/guide/en/elasticsearch/plugins/current/analysis-stempel.html)
- `ukrainian` - [analysis-ukrainian plugin](https://www.elastic.co/guide/en/elasticsearch/plugins/7.4/analysis-ukrainian.html)
- `vietnamese` - [analysis-vietnamese plugin](https://github.com/duydo/elasticsearch-analysis-vietnamese)
You can also use a Hunspell dictionary for stemming.
```ruby
class Product < ApplicationRecord
searchkick stemmer: {type: "hunspell", locale: "en_US"}
end
```
Disable stemming with:
```ruby
class Image < ApplicationRecord
searchkick stem: false
end
```
Exclude certain words from stemming with:
```ruby
class Image < ApplicationRecord
searchkick stem_exclusion: ["apples"]
end
```
Or change how words are stemmed:
```ruby
class Image < ApplicationRecord
searchkick stemmer_override: ["apples => other"]
end
```
### Synonyms
```ruby
class Product < ApplicationRecord
searchkick search_synonyms: [["pop", "soda"], ["burger", "hamburger"]]
end
```
Call `Product.reindex` after changing synonyms. Synonyms are applied at search time before stemming, and can be a single word or multiple words.
For directional synonyms, use:
```ruby
search_synonyms: ["lightbulb => halogenlamp"]
```
### Dynamic Synonyms
The above approach works well when your synonym list is static, but in practice, this is often not the case. When you analyze search conversions, you often want to add new synonyms without a full reindex.
#### Elasticsearch 7.3+ and OpenSearch
For Elasticsearch 7.3+ and OpenSearch, we recommend placing synonyms in a file on the search server (in the `config` directory). This allows you to reload synonyms without reindexing.
```txt
pop, soda
burger, hamburger
```
Then use:
```ruby
class Product < ApplicationRecord
searchkick search_synonyms: "synonyms.txt"
end
```
And reload with:
```ruby
Product.search_index.reload_synonyms
```
#### Elasticsearch < 7.3
You can use a library like [ActsAsTaggableOn](https://github.com/mbleigh/acts-as-taggable-on) and do:
```ruby
class Product < ApplicationRecord
acts_as_taggable
scope :search_import, -> { includes(:tags) }
def search_data
{
name_tagged: "#{name} #{tags.map(&:name).join(" ")}"
}
end
end
```
Search with:
```ruby
Product.search(query, fields: [:name_tagged])
```
### Misspellings
By default, Searchkick handles misspelled queries by returning results with an [edit distance](https://en.wikipedia.org/wiki/Levenshtein_distance) of one.
You can change this with:
```ruby
Product.search("zucini", misspellings: {edit_distance: 2}) # zucchini
```
To prevent poor precision and improve performance for correctly spelled queries (which should be a majority for most applications), Searchkick can first perform a search without misspellings, and if there are too few results, perform another with them.
```ruby
Product.search("zuchini", misspellings: {below: 5})
```
If there are fewer than 5 results, a 2nd search is performed with misspellings enabled. The result of this query is returned.
Turn off misspellings with:
```ruby
Product.search("zuchini", misspellings: false) # no zucchini
```
Specify which fields can include misspellings with:
```ruby
Product.search("zucini", fields: [:name, :color], misspellings: {fields: [:name]})
```
> When doing this, you must also specify fields to search
### Bad Matches
If a user searches `butter`, they may also get results for `peanut butter`. To prevent this, use:
```ruby
Product.search("butter", exclude: ["peanut butter"])
```
You can map queries and terms to exclude with:
```ruby
exclude_queries = {
"butter" => ["peanut butter"],
"cream" => ["ice cream", "whipped cream"]
}
Product.search(query, exclude: exclude_queries[query])
```
You can demote results by boosting by a factor less than one:
```ruby
Product.search("butter", boost_where: {category: {value: "pantry", factor: 0.5}})
```
### Emoji
Search :ice_cream::cake: and get `ice cream cake`!
Add this line to your application’s Gemfile:
```ruby
gem "gemoji-parser"
```
And use:
```ruby
Product.search("🍨🍰", emoji: true)
```
## Indexing
Control what data is indexed with the `search_data` method. Call `Product.reindex` after changing this method.
```ruby
class Product < ApplicationRecord
belongs_to :department
def search_data
{
name: name,
department_name: department.name,
on_sale: sale_price.present?
}
end
end
```
Searchkick uses `find_in_batches` to import documents. To eager load associations, use the `search_import` scope.
```ruby
class Product < ApplicationRecord
scope :search_import, -> { includes(:department) }
end
```
By default, all records are indexed. To control which records are indexed, use the `should_index?` method.
```ruby
class Product < ApplicationRecord
def should_index?
active # only index active records
end
end
```
If a reindex is interrupted, you can resume it with:
```ruby
Product.reindex(resume: true)
```
For large data sets, try [parallel reindexing](#parallel-reindexing).
### To Reindex, or Not to Reindex
#### Reindex
- when you install or upgrade searchkick
- change the `search_data` method
- change the `searchkick` method
#### No need to reindex
- app starts
### Strategies
There are four strategies for keeping the index synced with your database.
1. Inline (default)
Anytime a record is inserted, updated, or deleted
2. Asynchronous
Use background jobs for better performance
```ruby
class Product < ApplicationRecord
searchkick callbacks: :async
end
```
Jobs are added to a queue named `searchkick`.
3. Queuing
Push ids of records that need updated to a queue and reindex in the background in batches. This is more performant than the asynchronous method, which updates records individually. See [how to set up](#queuing).
4. Manual
Turn off automatic syncing
```ruby
class Product < ApplicationRecord
searchkick callbacks: false
end
```
And reindex a record or relation manually.
```ruby
product.reindex
# or
store.products.reindex(mode: :async)
```
You can also do bulk updates.
```ruby
Searchkick.callbacks(:bulk) do
Product.find_each(&:update_fields)
end
```
Or temporarily skip updates.
```ruby
Searchkick.callbacks(false) do
Product.find_each(&:update_fields)
end
```
Or override the model’s strategy.
```ruby
product.reindex(mode: :async) # :inline or :queue
```
### Associations
Data is **not** automatically synced when an association is updated. If this is desired, add a callback to reindex:
```ruby
class Image < ApplicationRecord
belongs_to :product
after_commit :reindex_product
def reindex_product
product.reindex
end
end
```
### Default Scopes
If you have a default scope that filters records, use the `should_index?` method to exclude them from indexing:
```ruby
class Product < ApplicationRecord
default_scope { where(deleted_at: nil) }
def should_index?
deleted_at.nil?
end
end
```
If you want to index and search filtered records, set:
```ruby
class Product < ApplicationRecord
searchkick unscope: true
end
```
## Intelligent Search
The best starting point to improve your search **by far** is to track searches and conversions. [Searchjoy](https://github.com/ankane/searchjoy) makes it easy.
```ruby
Product.search("apple", track: {user_id: current_user.id})
```
[See the docs](https://github.com/ankane/searchjoy) for how to install and use. Focus on top searches with a low conversion rate.
Searchkick can then use the conversion data to learn what users are looking for. If a user searches for “ice cream” and adds Ben & Jerry’s Chunky Monkey to the cart (our conversion metric at Instacart), that item gets a little more weight for similar searches. This can make a huge difference on the quality of your search.
Add conversion data with:
```ruby
class Product < ApplicationRecord
has_many :conversions, class_name: "Searchjoy::Conversion", as: :convertable
has_many :searches, class_name: "Searchjoy::Search", through: :conversions
searchkick conversions: [:conversions] # name of field
def search_data
{
name: name,
conversions: searches.group(:query).distinct.count(:user_id)
# {"ice cream" => 234, "chocolate" => 67, "cream" => 2}
}
end
end
```
Reindex and set up a cron job to add new conversions daily. For zero downtime deployment, temporarily set `conversions: false` in your search calls until the data is reindexed.
### Performant Conversions
A performant way to do conversions is to cache them to prevent N+1 queries. For Postgres, create a migration with:
```ruby
add_column :products, :search_conversions, :jsonb
```
For MySQL, use `:json`, and for others, use `:text` with a [JSON serializer](https://api.rubyonrails.org/classes/ActiveRecord/AttributeMethods/Serialization/ClassMethods.html).
Next, update your model. Create a separate method for conversion data so you can use [partial reindexing](#partial-reindexing).
```ruby
class Product < ApplicationRecord
searchkick conversions: [:conversions]
def search_data
{
name: name,
category: category
}.merge(conversions_data)
end
def conversions_data
{
conversions: search_conversions || {}
}
end
end
```
Deploy and reindex your data. For zero downtime deployment, temporarily set `conversions: false` in your search calls until the data is reindexed.
```ruby
Product.reindex
```
Then, create a job to update the conversions column and reindex records with new conversions. Here’s one you can use for Searchjoy:
```ruby
class UpdateConversionsJob < ApplicationJob
def perform(class_name, since: nil, update: true, reindex: true)
model = Searchkick.load_model(class_name)
# get records that have a recent conversion
recently_converted_ids =
Searchjoy::Conversion.where(convertable_type: class_name).where(created_at: since..)
.order(:convertable_id).distinct.pluck(:convertable_id)
# split into batches
recently_converted_ids.in_groups_of(1000, false) do |ids|
if update
# fetch conversions
conversions =
Searchjoy::Conversion.where(convertable_id: ids, convertable_type: class_name)
.joins(:search).where.not(searchjoy_searches: {user_id: nil})
.group(:convertable_id, :query).distinct.count(:user_id)
# group by record
conversions_by_record = {}
conversions.each do |(id, query), count|
(conversions_by_record[id] ||= {})[query] = count
end
# update conversions column
model.transaction do
conversions_by_record.each do |id, conversions|
model.where(id: id).update_all(search_conversions: conversions)
end
end
end
if reindex
# reindex conversions data
model.where(id: ids).reindex(:conversions_data)
end
end
end
end
```
Run the job:
```ruby
UpdateConversionsJob.perform_now("Product")
```
And set it up to run daily.
```ruby
UpdateConversionsJob.perform_later("Product", since: 1.day.ago)
```
## Personalized Results
Order results differently for each user. For example, show a user’s previously purchased products before other results.
```ruby
class Product < ApplicationRecord
def search_data
{
name: name,
orderer_ids: orders.pluck(:user_id) # boost this product for these users
}
end
end
```
Reindex and search with:
```ruby
Product.search("milk", boost_where: {orderer_ids: current_user.id})
```
## Instant Search / Autocomplete
Autocomplete predicts what a user will type, making the search experience faster and easier.
**Note:** To autocomplete on search terms rather than results, check out [Autosuggest](https://github.com/ankane/autosuggest).
**Note 2:** If you only have a few thousand records, don’t use Searchkick for autocomplete. It’s *much* faster to load all records into JavaScript and autocomplete there (eliminates network requests).
First, specify which fields use this feature. This is necessary since autocomplete can increase the index size significantly, but don’t worry - this gives you blazing faster queries.
```ruby
class Movie < ApplicationRecord
searchkick word_start: [:title, :director]
end
```
Reindex and search with:
```ruby
Movie.search("jurassic pa", fields: [:title], match: :word_start)
```
Typically, you want to use a JavaScript library like [typeahead.js](https://twitter.github.io/typeahead.js/) or [jQuery UI](https://jqueryui.com/autocomplete/).
#### Here’s how to make it work with Rails
First, add a route and controller action.
```ruby
class MoviesController < ApplicationController
def autocomplete
render json: Movie.search(params[:query], {
fields: ["title^5", "director"],
match: :word_start,
limit: 10,
load: false,
misspellings: {below: 5}
}).map(&:title)
end
end
```
**Note:** Use `load: false` and `misspellings: {below: n}` (or `misspellings: false`) for best performance.
Then add the search box and JavaScript code to a view.
```html
<input type="text" id="query" name="query" />
<script src="jquery.js"></script>
<script src="typeahead.bundle.js"></script>
<script>
var movies = new Bloodhound({
datumTokenizer: Bloodhound.tokenizers.whitespace,
queryTokenizer: Bloodhound.tokenizers.whitespace,
remote: {
url: '/movies/autocomplete?query=%QUERY',
wildcard: '%QUERY'
}
});
$('#query').typeahead(null, {
source: movies
});
</script>
```
## Suggestions
```ruby
class Product < ApplicationRecord
searchkick suggest: [:name] # fields to generate suggestions
end
```
Reindex and search with:
```ruby
products = Product.search("peantu butta", suggest: true)
products.suggestions # ["peanut butter"]
```
## Aggregations
[Aggregations](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations.html) provide aggregated search data.
```ruby
products = Product.search("chuck taylor", aggs: [:product_type, :gender, :brand])
products.aggs
```
By default, `where` conditions apply to aggregations.
```ruby
Product.search("wingtips", where: {color: "brandy"}, aggs: [:size])
# aggregations for brandy wingtips are returned
```
Change this with:
```ruby
Product.search("wingtips", where: {color: "brandy"}, aggs: [:size], smart_aggs: false)
# aggregations for all wingtips are returned
```
Set `where` conditions for each aggregation separately with:
```ruby
Product.search("wingtips", aggs: {size: {where: {color: "brandy"}}})
```
Limit
```ruby
Product.search("apples", aggs: {store_id: {limit: 10}})
```
Order
```ruby
Product.search("wingtips", aggs: {color: {order: {"_key" => "asc"}}}) # alphabetically
```
[All of these options are supported](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-terms-aggregation.html#search-aggregations-bucket-terms-aggregation-order)
Ranges
```ruby
price_ranges = [{to: 20}, {from: 20, to: 50}, {from: 50}]
Product.search("*", aggs: {price: {ranges: price_ranges}})
```
Minimum document count
```ruby
Product.search("apples", aggs: {store_id: {min_doc_count: 2}})
```
Script support
```ruby
Product.search("*", aggs: {color: {script: {source: "'Color: ' + _value"}}})
```
Date histogram
```ruby
Product.search("pear", aggs: {products_per_year: {date_histogram: {field: :created_at, interval: :year}}})
```
For other aggregation types, including sub-aggregations, use `body_options`:
```ruby
Product.search("orange", body_options: {aggs: {price: {histogram: {field: :price, interval: 10}}}})
```
## Highlight
Specify which fields to index with highlighting.
```ruby
class Band < ApplicationRecord
searchkick highlight: [:name]
end
```
Highlight the search query in the results.
```ruby
bands = Band.search("cinema", highlight: true)
```
View the highlighted fields with:
```ruby
bands.with_highlights.each do |band, highlights|
highlights[:name] # "Two Door <em>Cinema</em> Club"
end
```
To change the tag, use:
```ruby
Band.search("cinema", highlight: {tag: "<strong>"})
```
To highlight and search different fields, use:
```ruby
Band.search("cinema", fields: [:name], highlight: {fields: [:description]})
```
By default, the entire field is highlighted. To get small snippets instead, use:
```ruby
bands = Band.search("cinema", highlight: {fragment_size: 20})
bands.with_highlights(multiple: true).each do |band, highlights|
highlights[:name].join(" and ")
end
```
Additional options can be specified for each field:
```ruby
Band.search("cinema", fields: [:name], highlight: {fields: {name: {fragment_size: 200}}})
```
You can find available highlight options in the [Elasticsearch reference](https://www.elastic.co/guide/en/elasticsearch/reference/current/highlighting.html).
## Similar Items
Find similar items.
```ruby
product = Product.first
product.similar(fields: [:name], where: {size: "12 oz"})
```
## Geospatial Searches
```ruby
class Restaurant < ApplicationRecord
searchkick locations: [:location]
def search_data
attributes.merge(location: {lat: latitude, lon: longitude})
end
end
```
Reindex and search with:
```ruby
Restaurant.search("pizza", where: {location: {near: {lat: 37, lon: -114}, within: "100mi"}}) # or 160km
```
Bounded by a box
```ruby
Restaurant.search("sushi", where: {location: {top_left: {lat: 38, lon: -123}, bottom_right: {lat: 37, lon: -122}}})
```
**Note:** `top_right` and `bottom_left` also work
Bounded by a polygon
```ruby
Restaurant.search("dessert", where: {location: {geo_polygon: {points: [{lat: 38, lon: -123}, {lat: 39, lon: -123}, {lat: 37, lon: 122}]}}})
```
### Boost By Distance
Boost results by distance - closer results are boosted more
```ruby
Restaurant.search("noodles", boost_by_distance: {location: {origin: {lat: 37, lon: -122}}})
```
Also supports [additional options](https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-function-score-query.html#function-decay)
```ruby
Restaurant.search("wings", boost_by_distance: {location: {origin: {lat: 37, lon: -122}, function: "linear", scale: "30mi", decay: 0.5}})
```
### Geo Shapes
You can also index and search geo shapes.
```ruby
class Restaurant < ApplicationRecord
searchkick geo_shape: [:bounds]
def search_data
attributes.merge(
bounds: {
type: "envelope",
coordinates: [{lat: 4, lon: 1}, {lat: 2, lon: 3}]
}
)
end
end
```
See the [Elasticsearch documentation](https://www.elastic.co/guide/en/elasticsearch/reference/current/geo-shape.html) for details.
Find shapes intersecting with the query shape
```ruby
Restaurant.search("soup", where: {bounds: {geo_shape: {type: "polygon", coordinates: [[{lat: 38, lon: -123}, ...]]}}})
```
Falling entirely within the query shape
```ruby
Restaurant.search("salad", where: {bounds: {geo_shape: {type: "circle", relation: "within", coordinates: {lat: 38, lon: -123}, radius: "1km"}}})
```
Not touching the query shape
```ruby
Restaurant.search("burger", where: {bounds: {geo_shape: {type: "envelope", relation: "disjoint", coordinates: [{lat: 38, lon: -123}, {lat: 37, lon: -122}]}}})
```
## Inheritance
Searchkick supports single table inheritance.
```ruby
class Dog < Animal
end
```
In your parent model, set:
```ruby
class Animal < ApplicationRecord
searchkick inheritance: true
end
```
The parent and child model can both reindex.
```ruby
Animal.reindex
Dog.reindex # equivalent, all animals reindexed
```
And to search, use:
```ruby
Animal.search("*") # all animals
Dog.search("*") # just dogs
Animal.search("*", type: [Dog, Cat]) # just cats and dogs
```
**Notes:**
1. The `suggest` option retrieves suggestions from the parent at the moment.
```ruby
Dog.search("airbudd", suggest: true) # suggestions for all animals
```
2. This relies on a `type` field that is automatically added to the indexed document. Be wary of defining your own `type` field in `search_data`, as it will take precedence.
## Debugging Queries
To help with debugging queries, you can use:
```ruby
Product.search("soap", debug: true)
```
This prints useful info to `stdout`.
See how the search server scores your queries with:
```ruby
Product.search("soap", explain: true).response
```
See how the search server tokenizes your queries with:
```ruby
Product.search_index.tokens("Dish Washer Soap", analyzer: "searchkick_index")
# ["dish", "dishwash", "washer", "washersoap", "soap"]
Product.search_index.tokens("dishwasher soap", analyzer: "searchkick_search")
# ["dishwashersoap"] - no match
Product.search_index.tokens("dishwasher soap", analyzer: "searchkick_search2")
# ["dishwash", "soap"] - match!!
```
Partial matches
```ruby
Product.search_index.tokens("San Diego", analyzer: "searchkick_word_start_index")
# ["s", "sa", "san", "d", "di", "die", "dieg", "diego"]
Product.search_index.tokens("dieg", analyzer: "searchkick_word_search")
# ["dieg"] - match!!
```
See the [complete list of analyzers](lib/searchkick/index_options.rb#L36).
## Testing
As you iterate on your search, it’s a good idea to add tests.
For performance, only enable Searchkick callbacks for the tests that need it.
### Parallel Tests
Rails 6 enables parallel tests by default. Add to your `test/test_helper.rb`:
```ruby
class ActiveSupport::TestCase
parallelize_setup do |worker|
Searchkick.index_suffix = worker
# reindex models
Product.reindex
# and disable callbacks
Searchkick.disable_callbacks
end
end
```
And use:
```ruby
class ProductTest < ActiveSupport::TestCase
def setup
Searchkick.enable_callbacks
end
def teardown
Searchkick.disable_callbacks
end
def test_search
Product.create!(name: "Apple")
Product.search_index.refresh
assert_equal ["Apple"], Product.search("apple").map(&:name)
end
end
```
### Minitest
Add to your `test/test_helper.rb`:
```ruby
# reindex models
Product.reindex
# and disable callbacks
Searchkick.disable_callbacks
```
And use:
```ruby
class ProductTest < Minitest::Test
def setup
Searchkick.enable_callbacks
end
def teardown
Searchkick.disable_callbacks
end
def test_search
Product.create!(name: "Apple")
Product.search_index.refresh
assert_equal ["Apple"], Product.search("apple").map(&:name)
end
end
```
### RSpec
Add to your `spec/spec_helper.rb`:
```ruby
RSpec.configure do |config|
config.before(:suite) do
# reindex models
Product.reindex
# and disable callbacks
Searchkick.disable_callbacks
end
config.around(:each, search: true) do |example|
Searchkick.callbacks(nil) do
example.run
end
end
end
```
And use:
```ruby
describe Product, search: true do
it "searches" do
Product.create!(name: "Apple")
Product.search_index.refresh
assert_equal ["Apple"], Product.search("apple").map(&:name)
end
end
```
### Factory Bot
Use a trait and an after `create` hook for each indexed model:
```ruby
FactoryBot.define do
factory :product do
# ...
# Note: This should be the last trait in the list so `reindex` is called
# after all the other callbacks complete.
trait :reindex do
after(:create) do |product, _evaluator|
product.reindex(refresh: true)
end
end
end
end
# use it
FactoryBot.create(:product, :some_trait, :reindex, some_attribute: "foo")
```
### GitHub Actions
Check out [setup-elasticsearch](https://github.com/ankane/setup-elasticsearch) for an easy way to install Elasticsearch:
```yml
- uses: ankane/setup-elasticsearch@v1
```
And [setup-opensearch](https://github.com/ankane/setup-opensearch) for an easy way to install OpenSearch:
```yml
- uses: ankane/setup-opensearch@v1
```
## Deployment
For the search server, Searchkick uses `ENV["ELASTICSEARCH_URL"]` for Elasticsearch and `ENV["OPENSEARCH_URL"]` for OpenSearch. This defaults to `http://localhost:9200`.
- [Elastic Cloud](#elastic-cloud)
- [Heroku](#heroku)
- [Amazon OpenSearch Service](#amazon-opensearch-service)
- [Self-Hosted and Other](#self-hosted-and-other)
### Elastic Cloud
Create an initializer `config/initializers/elasticsearch.rb` with:
```ruby
ENV["ELASTICSEARCH_URL"] = "https://user:password@host:port"
```
Then deploy and reindex:
```sh
rake searchkick:reindex:all
```
### Heroku
Choose an add-on: [Bonsai](https://elements.heroku.com/addons/bonsai), [SearchBox](https://elements.heroku.com/addons/searchbox), or [Elastic Cloud](https://elements.heroku.com/addons/foundelasticsearch).
For Elasticsearch on Bonsai:
```sh
heroku addons:create bonsai
heroku config:set ELASTICSEARCH_URL=`heroku config:get BONSAI_URL`
```
For OpenSearch on Bonsai:
```sh
heroku addons:create bonsai --engine=opensearch
heroku config:set OPENSEARCH_URL=`heroku config:get BONSAI_URL`
```
For SearchBox:
```sh
heroku addons:create searchbox:starter
heroku config:set ELASTICSEARCH_URL=`heroku config:get SEARCHBOX_URL`
```
For Elastic Cloud (previously Found):
```sh
heroku addons:create foundelasticsearch
heroku addons:open foundelasticsearch
```
Visit the Shield page and reset your password. You’ll need to add the username and password to your url. Get the existing url with:
```sh
heroku config:get FOUNDELASTICSEARCH_URL
```
And add `elastic:password@` right after `https://` and add port `9243` at the end:
```sh
heroku config:set ELASTICSEARCH_URL=https://elastic:
[email protected]:9243
```
Then deploy and reindex:
```sh
heroku run rake searchkick:reindex:all
```
### Amazon OpenSearch Service
Create an initializer `config/initializers/opensearch.rb` with:
```ruby
ENV["OPENSEARCH_URL"] = "https://es-domain-1234.us-east-1.es.amazonaws.com:443"
```
To use signed requests, include in your Gemfile:
```ruby
gem "faraday_middleware-aws-sigv4"
```
and add to your initializer:
```ruby
Searchkick.aws_credentials = {
access_key_id: ENV["AWS_ACCESS_KEY_ID"],
secret_access_key: ENV["AWS_SECRET_ACCESS_KEY"],
region: "us-east-1"
}
```
Then deploy and reindex:
```sh
rake searchkick:reindex:all
```
### Self-Hosted and Other
Create an initializer with:
```ruby
ENV["ELASTICSEARCH_URL"] = "https://user:password@host:port"
# or
ENV["OPENSEARCH_URL"] = "https://user:password@host:port"
```
Then deploy and reindex:
```sh
rake searchkick:reindex:all
```
### Data Protection
We recommend encrypting data at rest and in transit (even inside your own network). This is especially important if you send [personal data](https://en.wikipedia.org/wiki/Personally_identifiable_information) of your users to the search server.
Bonsai, Elastic Cloud, and Amazon OpenSearch Service all support encryption at rest and HTTPS.
### Automatic Failover
Create an initializer with multiple hosts:
```ruby
ENV["ELASTICSEARCH_URL"] = "https://user:password@host1,https://user:password@host2"
# or
ENV["OPENSEARCH_URL"] = "https://user:password@host1,https://user:password@host2"
```
### Client Options
Create an initializer with:
```ruby
Searchkick.client_options[:reload_connections] = true
```
See the docs for [Elasticsearch](https://www.elastic.co/guide/en/elasticsearch/client/ruby-api/current/advanced-config.html) or [Opensearch](https://rubydoc.info/gems/opensearch-transport#configuration) for a complete list of options.
### Lograge
Add the following to `config/environments/production.rb`:
```ruby
config.lograge.custom_options = lambda do |event|
options = {}
options[:search] = event.payload[:searchkick_runtime] if event.payload[:searchkick_runtime].to_f > 0
options
end
```
See [Production Rails](https://github.com/ankane/production_rails) for other good practices.
## Performance
### JSON Generation
Significantly increase performance with faster JSON generation. Add [Oj](https://github.com/ohler55/oj) to your Gemfile.
```ruby
gem "oj"
```
This speeds up all JSON generation and parsing in your application (automatically!)
### Persistent HTTP Connections
Significantly increase performance with persistent HTTP connections. Add [Typhoeus](https://github.com/typhoeus/typhoeus) to your Gemfile and it’ll automatically be used.
```ruby
gem "typhoeus"
```
To reduce log noise, create an initializer with:
```ruby
Ethon.logger = Logger.new(nil)
```
If you run into issues on Windows, check out [this post](https://www.rastating.com/fixing-issues-in-typhoeus-and-httparty-on-windows/).
### Searchable Fields
By default, all string fields are searchable (can be used in `fields` option). Speed up indexing and reduce index size by only making some fields searchable.
```ruby
class Product < ApplicationRecord
searchkick searchable: [:name]
end
```
### Filterable Fields
By default, all string fields are filterable (can be used in `where` option). Speed up indexing and reduce index size by only making some fields filterable.
```ruby
class Product < ApplicationRecord
searchkick filterable: [:brand]
end
```
**Note:** Non-string fields are always filterable and should not be passed to this option.
### Parallel Reindexing
For large data sets, you can use background jobs to parallelize reindexing.
```ruby
Product.reindex(mode: :async)
# {index_name: "products_production_20250111210018065"}
```
Once the jobs complete, promote the new index with:
```ruby
Product.search_index.promote(index_name)
```
You can optionally track the status with Redis:
```ruby
Searchkick.redis = Redis.new
```
And use:
```ruby
Searchkick.reindex_status(index_name)
```
You can also have Searchkick wait for reindexing to complete
```ruby
Product.reindex(mode: :async, wait: true)
```
You can use [ActiveJob::TrafficControl](https://github.com/nickelser/activejob-traffic_control) to control concurrency. Install the gem:
```ruby
gem "activejob-traffic_control", ">= 0.1.3"
```
And create an initializer with:
```ruby
ActiveJob::TrafficControl.client = Searchkick.redis
class Searchkick::BulkReindexJob
concurrency 3
end
```
This will allow only 3 jobs to run at once.
### Refresh Interval
You can specify a longer refresh interval while reindexing to increase performance.
```ruby
Product.reindex(mode: :async, refresh_interval: "30s")
```
**Note:** This only makes a noticeable difference with parallel reindexing.
When promoting, have it restored to the value in your mapping (defaults to `1s`).
```ruby
Product.search_index.promote(index_name, update_refresh_interval: true)
```
### Queuing
Push ids of records needing reindexing to a queue and reindex in bulk for better performance. First, set up Redis in an initializer. We recommend using [connection_pool](https://github.com/mperham/connection_pool).
```ruby
Searchkick.redis = ConnectionPool.new { Redis.new }
```
And ask your models to queue updates.
```ruby
class Product < ApplicationRecord
searchkick callbacks: :queue
end
```
Then, set up a background job to run.
```ruby
Searchkick::ProcessQueueJob.perform_later(class_name: "Product")
```
You can check the queue length with:
```ruby
Product.search_index.reindex_queue.length
```
For more tips, check out [Keeping Elasticsearch in Sync](https://www.elastic.co/blog/found-keeping-elasticsearch-in-sync).
### Routing
Searchkick supports [routing](https://www.elastic.co/blog/customizing-your-document-routing), which can significantly speed up searches.
```ruby
class Business < ApplicationRecord
searchkick routing: true
def search_routing
city_id
end
end
```
Reindex and search with:
```ruby
Business.search("ice cream", routing: params[:city_id])
```
### Partial Reindexing
Reindex a subset of attributes to reduce time spent generating search data and cut down on network traffic.
```ruby
class Product < ApplicationRecord
def search_data
{
name: name,
category: category
}.merge(prices_data)
end
def prices_data
{
price: price,
sale_price: sale_price
}
end
end
```
And use:
```ruby
Product.reindex(:prices_data)
```
## Advanced
Searchkick makes it easy to use the Elasticsearch or OpenSearch DSL on its own.
### Advanced Mapping
Create a custom mapping:
```ruby
class Product < ApplicationRecord
searchkick mappings: {
properties: {
name: {type: "keyword"}
}
}
end
```
**Note:** If you use a custom mapping, you'll need to use [custom searching](#advanced-search) as well.
To keep the mappings and settings generated by Searchkick, use:
```ruby
class Product < ApplicationRecord
searchkick merge_mappings: true, mappings: {...}
end
```
### Advanced Search
And use the `body` option to search:
```ruby
products = Product.search(body: {query: {match: {name: "milk"}}})
```
View the response with:
```ruby
products.response
```
To modify the query generated by Searchkick, use:
```ruby
products = Product.search("milk", body_options: {min_score: 1})
```
or
```ruby
products =
Product.search("apples") do |body|
body[:min_score] = 1
end
```
### Client
To access the `Elasticsearch::Client` or `OpenSearch::Client` directly, use:
```ruby
Searchkick.client
```
## Multi Search
To batch search requests for performance, use:
```ruby
products = Product.search("snacks")
coupons = Coupon.search("snacks")
Searchkick.multi_search([products, coupons])
```
Then use `products` and `coupons` as typical results.
**Note:** Errors are not raised as with single requests. Use the `error` method on each query to check for errors.
## Multiple Models
Search across multiple models with:
```ruby
Searchkick.search("milk", models: [Product, Category])
```
Boost specific models with:
```ruby
indices_boost: {Category => 2, Product => 1}
```
## Multi-Tenancy
Check out [this great post](https://www.tiagoamaro.com.br/2014/12/11/multi-tenancy-with-searchkick/) on the [Apartment](https://github.com/influitive/apartment) gem. Follow a similar pattern if you use another gem.
## Scroll API
Searchkick also supports the [scroll API](https://www.elastic.co/guide/en/elasticsearch/reference/current/paginate-search-results.html#scroll-search-results). Scrolling is not intended for real time user requests, but rather for processing large amounts of data.
```ruby
Product.search("*", scroll: "1m").scroll do |batch|
# process batch ...
end
```
You can also scroll batches manually.
```ruby
products = Product.search("*", scroll: "1m")
while products.any?
# process batch ...
products = products.scroll
end
products.clear_scroll
```
## Deep Paging
By default, Elasticsearch and OpenSearch limit paging to the first 10,000 results. [Here’s why](https://www.elastic.co/guide/en/elasticsearch/guide/current/pagination.html). We don’t recommend changing this, but if you really need all results, you can use:
```ruby
class Product < ApplicationRecord
searchkick deep_paging: true
end
```
If you just need an accurate total count, you can instead use:
```ruby
Product.search("pears", body_options: {track_total_hits: true})
```
## Nested Data
To query nested data, use dot notation.
```ruby
Product.search("san", fields: ["store.city"], where: {"store.zip_code" => 12345})
```
## Nearest Neighbor Search
*Available for Elasticsearch 8.6+ and OpenSearch 2.4+*
```ruby
class Product < ApplicationRecord
searchkick knn: {embedding: {dimensions: 3, distance: "cosine"}}
end
```
Also supports `euclidean` and `inner_product`
Reindex and search with:
```ruby
Product.search(knn: {field: :embedding, vector: [1, 2, 3]}, limit: 10)
```
## Semantic Search
First, add [nearest neighbor search](#nearest-neighbor-search) to your model
```ruby
class Product < ApplicationRecord
searchkick knn: {embedding: {dimensions: 768, distance: "cosine"}}
end
```
Generate an embedding for each record (you can use an external service or a library like [Informers](https://github.com/ankane/informers))
```ruby
embed = Informers.pipeline("embedding", "Snowflake/snowflake-arctic-embed-m-v1.5")
embed_options = {model_output: "sentence_embedding", pooling: "none"} # specific to embedding model
Product.find_each do |product|
embedding = embed.(product.name, **embed_options)
product.update!(embedding: embedding)
end
```
For search, generate an embedding for the query (the query prefix is specific to the [embedding model](https://huggingface.co/Snowflake/snowflake-arctic-embed-m-v1.5))
```ruby
query_prefix = "Represent this sentence for searching relevant passages: "
query_embedding = embed.(query_prefix + query, **embed_options)
```
And perform nearest neighbor search
```ruby
Product.search(knn: {field: :embedding, vector: query_embedding}, limit: 20)
```
See a [full example](examples/semantic.rb)
## Hybrid Search
Perform keyword search and semantic search in parallel
```ruby
keyword_search = Product.search(query, limit: 20)
semantic_search = Product.search(knn: {field: :embedding, vector: query_embedding}, limit: 20)
Searchkick.multi_search([keyword_search, semantic_search])
```
To combine the results, use Reciprocal Rank Fusion (RRF)
```ruby
Searchkick::Reranking.rrf(keyword_search, semantic_search).first(5)
```
Or a reranking model
```ruby
rerank = Informers.pipeline("reranking", "mixedbread-ai/mxbai-rerank-xsmall-v1")
results = (keyword_search.to_a + semantic_search.to_a).uniq
rerank.(query, results.map(&:name)).first(5).map { |v| results[v[:doc_id]] }
```
See a [full example](examples/hybrid.rb)
## Reference
Reindex one record
```ruby
product = Product.find(1)
product.reindex
```
Reindex multiple records
```ruby
Product.where(store_id: 1).reindex
```
Reindex associations
```ruby
store.products.reindex
```
Remove old indices
```ruby
Product.search_index.clean_indices
```
Use custom settings
```ruby
class Product < ApplicationRecord
searchkick settings: {number_of_shards: 3}
end
```
Use a different index name
```ruby
class Product < ApplicationRecord
searchkick index_name: "products_v2"
end
```
Use a dynamic index name
```ruby
class Product < ApplicationRecord
searchkick index_name: -> { "#{name.tableize}-#{I18n.locale}" }
end
```
Prefix the index name
```ruby
class Product < ApplicationRecord
searchkick index_prefix: "datakick"
end
```
For all models
```ruby
Searchkick.index_prefix = "datakick"
```
Use a different term for boosting by conversions
```ruby
Product.search("banana", conversions_term: "organic banana")
```
Multiple conversion fields
```ruby
class Product < ApplicationRecord
has_many :searches, class_name: "Searchjoy::Search"
# searchkick also supports multiple "conversions" fields
searchkick conversions: ["unique_user_conversions", "total_conversions"]
def search_data
{
name: name,
unique_user_conversions: searches.group(:query).distinct.count(:user_id),
# {"ice cream" => 234, "chocolate" => 67, "cream" => 2}
total_conversions: searches.group(:query).count
# {"ice cream" => 412, "chocolate" => 117, "cream" => 6}
}
end
end
```
and during query time:
```ruby
Product.search("banana") # boost by both fields (default)
Product.search("banana", conversions: "total_conversions") # only boost by total_conversions
Product.search("banana", conversions: false) # no conversion boosting
```
Change timeout
```ruby
Searchkick.timeout = 15 # defaults to 10
```
Set a lower timeout for searches
```ruby
Searchkick.search_timeout = 3
```
Change the search method name
```ruby
Searchkick.search_method_name = :lookup
```
Change search queue name
```ruby
Searchkick.queue_name = :search_reindex
```
Eager load associations
```ruby
Product.search("milk", includes: [:brand, :stores])
```
Eager load different associations by model
```ruby
Searchkick.search("*", models: [Product, Store], model_includes: {Product => [:store], Store => [:product]})
```
Run additional scopes on results
```ruby
Product.search("milk", scope_results: ->(r) { r.with_attached_images })
```
Specify default fields to search
```ruby
class Product < ApplicationRecord
searchkick default_fields: [:name]
end
```
Turn off special characters
```ruby
class Product < ApplicationRecord
# A will not match Ä
searchkick special_characters: false
end
```
Turn on stemming for conversions
```ruby
class Product < ApplicationRecord
searchkick stem_conversions: true
end
```
Make search case-sensitive
```ruby
class Product < ApplicationRecord
searchkick case_sensitive: true
end
```
**Note:** If misspellings are enabled (default), results with a single character case difference will match. Turn off misspellings if this is not desired.
Change import batch size
```ruby
class Product < ApplicationRecord
searchkick batch_size: 200 # defaults to 1000
end
```
Create index without importing
```ruby
Product.reindex(import: false)
```
Use a different id
```ruby
class Product < ApplicationRecord
def search_document_id
custom_id
end
end
```
Add [request parameters](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-search.html#search-search-api-query-params) like `search_type`
```ruby
Product.search("carrots", request_params: {search_type: "dfs_query_then_fetch"})
```
Set options across all models
```ruby
Searchkick.model_options = {
batch_size: 200
}
```
Reindex conditionally
```ruby
class Product < ApplicationRecord
searchkick callbacks: false
# add the callbacks manually
after_commit :reindex, if: -> (model) { model.previous_changes.key?("name") } # use your own condition
end
```
Reindex all models - Rails only
```sh
rake searchkick:reindex:all
```
Turn on misspellings after a certain number of characters
```ruby
Product.search("api", misspellings: {prefix_length: 2}) # api, apt, no ahi
```
**Note:** With this option, if the query length is the same as `prefix_length`, misspellings are turned off with Elasticsearch 7 and OpenSearch 1
```ruby
Product.search("ah", misspellings: {prefix_length: 2}) # ah, no aha
```
BigDecimal values are indexed as floats by default so they can be used for boosting. Convert them to strings to keep full precision.
```ruby
class Product < ApplicationRecord
def search_data
{
units: units.to_s("F")
}
end
end
```
## Gotchas
### Consistency
Elasticsearch and OpenSearch are eventually consistent, meaning it can take up to a second for a change to reflect in search. You can use the `refresh` method to have it show up immediately.
```ruby
product.save!
Product.search_index.refresh
```
### Inconsistent Scores
Due to the distributed nature of Elasticsearch and OpenSearch, you can get incorrect results when the number of documents in the index is low. You can [read more about it here](https://www.elastic.co/blog/understanding-query-then-fetch-vs-dfs-query-then-fetch). To fix this, do:
```ruby
class Product < ApplicationRecord
searchkick settings: {number_of_shards: 1}
end
```
For convenience, this is set by default in the test environment.
## History
View the [changelog](https://github.com/ankane/searchkick/blob/master/CHANGELOG.md).
## Thanks
Thanks to Karel Minarik for [Elasticsearch Ruby](https://github.com/elasticsearch/elasticsearch-ruby) and [Tire](https://github.com/karmi/retire), Jaroslav Kalistsuk for [zero downtime reindexing](https://gist.github.com/jarosan/3124884), and Alex Leschenko for [Elasticsearch autocomplete](https://github.com/leschenko/elasticsearch_autocomplete).
## Contributing
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- [Report bugs](https://github.com/ankane/searchkick/issues)
- Fix bugs and [submit pull requests](https://github.com/ankane/searchkick/pulls)
- Write, clarify, or fix documentation
- Suggest or add new features
To get started with development:
```sh
git clone https://github.com/ankane/searchkick.git
cd searchkick
bundle install
bundle exec rake test
```
Feel free to open an issue to get feedback on your idea before spending too much time on it.
", Assign "at most 3 tags" to the expected json: {"id":"4385","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"