It's the middle of October and more than time for an update on how Hacktoberfest is going at Meilisearch.

Shared objectives update
------------------------

[As mentioned](/blog/contribute-hacktoberfest-2021/)hen Hacktoberfest started, we're setting **shared objectives** that will **benefit everyone**. Upon reaching each objective, we will contribute to a few organizations or support people we think are doing great work.

### Open-source maintainers

We chose open-source for our project to share a high-quality search solution, accessible to all, no matter their financial means. Sharing is the basis of what we do. [Meilisearch](https://github.com/meilisearch/MeiliSearch) and [milli](https://github.com/meilisearch/milli) (Meilisearch's core engine) [have](https://github.com/meilisearch/MeiliSearch/blob/4bacc8e47d52f95a871028b0179b3dd4e2f9682d/meilisearch-http/Cargo.toml#L77-L81) [many](https://github.com/meilisearch/milli/blob/6e3b869e6a4d33bc814ebafe80d434035139e97d/milli/Cargo.toml#L7-L50) [dependencies](https://github.com/meilisearch/MeiliSearch/blob/4bacc8e47d52f95a871028b0179b3dd4e2f9682d/meilisearch-http/Cargo.toml#L24-L75), and most of them are other open-source projects. Their maintainers are not all part of large companies. By supporting some of these maintainers, we're contributing to open source and helping these developers to improve the projects we depend on.

These developers are the primary maintainers of:

*   [rust-sipash](https://github.com/jedisct1/rust-siphash) - [maintainer](https://github.com/jedisct1)
*   [vergen](https://github.com/rustyhorde/vergen) - [maintainer](https://github.com/CraZySacX)
*   [pin-project](https://github.com/taiki-e/pin-project) - [maintainer](https://github.com/taiki-e)

### Climate activists

We are aware that Meilisearch has an impact on our planet. We use servers, large datasets, computational power, all of which contribute to global warming. This is something we are not comfortable with, but it is an unavoidable aspect of being a tech company.

That's why we will support three organizations tackling the challenges of climate change:

*   [WWF](https://www.worldwildlife.org/)
*   [Surfriders Foundation Europe](https://surfrider.eu/en/)
*   [Reforest'Action](https://www.reforestaction.com/en)

### Organizations that promote diversity in tech

Meilisearch grows thanks to each team member's personality, skills, and experience. Having [different perspectives](https://www.welcometothejungle.com/fr/companies/meilisearch/values) in organizations leads to better decisions and is the only way to build a long-lasting company.

We will support three organizations that strive for diversity and inclusivity in software engineering:

*   [Black Girls Code](https://wearebgc.org/)
*   [Out in Tech](https://outintech.com/)
*   [Techfugees](https://techfugees.com/fr/)

### How to unlock the perks?

There are **three stages**. We will collectively reach them if the number of contributions to [Meilisearch open-source repositories](https://github.com/search?q=topic%3Ahacktoberfest+org%3Ameilisearch&type=Repositories) is high enough. Each stage will unlock a larger amount of money for these three groups we want to support.

![](https://unable-actionable-car.media.strapiapp.com/PR_a742efd3bd.png)

To get the total number of contributions, we will sum up the number of Hacktoberfest-related Pull Requests (PRs) merged in Meilisearch repositories at the end of the month. And we will add the last PRs not yet merged, but tagged with the `hacktoberfest-accepted` label.

In 2020, we had **49 PRs** merged during Hacktoberfest.  
This year, every 49 PRs merged, we will reach a new stage and **add 500€** to the financial support of each of the three groups.

We are already tracking the number of contributions: on October 20th, we had 114 PRs merged since the beginning of Hacktoberfest. Stage 1 & 2 have already been reached 🎉. We'll find a stretch goal later if we're able to reach stage 3 🤞.

A new way to contribute: Awesome Meilisearch
--------------------------------------------

To help you reach these stages, we're adding a new way to increase the number of contributions. You will still have to get a PR merged, but this PR does not have to close an issue.

We recently created the [**awesome-meilisearch**](https://github.com/meilisearch/awesome-meilisearch) repository. It contains a curated list of awesome Meilisearch resources, based on the [awesome list template](https://github.com/sindresorhus/awesome/blob/main/awesome.md).You can contribute to Meilisearch's Hacktoberfest goals by [adding new resources](https://github.com/meilisearch/awesome-meilisearch/blob/main/CONTRIBUTING.md) to this repository. These resources have to be links to awesome blog posts, tutorials, demos, guides, talks, or just about anything else that teaches people how to do cool things with Meilisearch.

All accepted contributions qualify for the shared goals count!

We're counting on you!
----------------------

Consider keeping on contributing to Meilisearch repositories once you have successfully participated in Hacktoberfest. If you increase the number of merged PRs, you will help unlock new perks that benefit everyone.

Mid-October Hacktoberfest update

This month’s release brings you geosearch and support for CSV and NDJSON payloads! You can read the full [changelog](https://github.com/meilisearch/MeiliSearch/releases/tag/v0.23.1), but let's take a look at some of the main and breaking changes.

New feature: Geosearch
======================

Meilisearch v0.23 supports geosearch. This allows you to filter and sort results based on their location.

To start using this feature, the `_geo` field must be present in your indexed documents and added to either the `filterableAttributes` or `sortableAttributes` list, depending on the type of operation you’d like to perform.

To filter your results so that they are within a certain area, you can use the built-in `_geoRadius` filter rule. Let’s say we're in the center of Muscat and want to view restaurants that are within two kilometers:

```bash
curl  
    -X POST 'http://localhost:7700/indexes/restaurants/search' \
    --data-binary '{ 
		"filter": "_geoRadius(23.5880, 58.3829, 2000)" 
	}'
```

`_geoRadius` establishes a circular area based on a central point and a radius. It requires three parameters: `lat`, `lng`, and `distance_in_meters`—the latitude, longitude, and distance in meters respectively.

You can also sort search results in ascending or descending order based on their distance from a geographic location using `_geoPoint`_._ Let’s say you want to order documents based on how close they are to the Eiffel Tower:

```bash
curl \
    -X POST 'http://localhost:7700/indexes/restaurants/search' \
	-H 'Content-type:application/json'
	--data-binary '{
	  "sort": "_geoPoint(48.8583701,2.2922926):asc" 
	}`
```

The search response will return an extra field called `_geoDistance`. This is the distance in meters computed from the `_geoPoint` and the `_geo` coordinates of the search results.

New feature: support for NDJSON and CSV payloads
================================================

Meilisearch now accepts CSV and NDJSON along with JSON as data sources. You will now need to specify a Content-Type header for HTTP requests through tools like `curl`.

Both CSV and NDJSON offer better indexation performance, consume less RAM and are not as CPU-intensive as JSON. NDJSON is easier to validate and, unlike CSV, can handle nested structures.  

Breaking change: Content-Type headers are now mandatory
=======================================================

Since Meilisearch now supports JSON, NDJSON, and CSV, you need to specify content headers for HTTP requests through tools like `curl`.

*   `Content-Type: application/json` for JSON
*   `Content-Type: application/x-ndjson` for NDJSON
*   `Content-Type: text/csv` for CSV

An example of the JSON header when creating an index:

```bash
curl \
    -X POST 'http://localhost:7700/indexes' \
    -H 'Content-Type: application/json' \
    --data-binary '{
      "uid": "movies",
      "primaryKey": "movie_id"
    }'
```

Contributors
============

A big thank you to all our contributors! We wouldn't have made it here without your support. This month, we want to send a special shout out to [@anirudhRowjee](https://github.com/anirudhRowjee), [@felixonmars](https://github.com/felixonmars), [@happysalada](https://github.com/happysalada), [@kappa-wingman](https://github.com/kappa-wingman), [@k-nasa](https://github.com/k-nasa), and [@shekhirin](https://github.com/shekhirin).

* * *

And that's all folks! Remember to check out the [changelog](https://github.com/meilisearch/MeiliSearch/releases/tag/v0.23.1) for the full release notes and see you next month!

What's new in v0.23

What is Hacktoberfest?
----------------------

[Hacktoberfest](https://hacktoberfest.digitalocean.com/) is an annual event that runs over October. Instead of celebrating the Bavarian culture (and sometimes drinking too many beers), this event aims at **supporting the open source community**.

2021 marks the eighth anniversary of the event launched by [DigitalOcean](https://www.digitalocean.com/). Over the years, Hacktoberfest has had a seminal role: it has given enough confidence to many developers to become a part of the open-source community. In 2020, around 170,000 developers participated in Hacktoberfest.

Why should you participate?
---------------------------

There are many different reasons why you should [contribute to open source](https://blog.shahednasser.com/how-to-participate-in-hacktoberfest-2021/#as-a-participant). But Hacktoberfest is about joining the community in a mutual effort to drive the growth of open source.

Your contributions are very valuable to any open-source project. Some of our most used tools were born outside the Meilisearch team, and we could not be grateful enough for the efforts of our open-source contributors.

And if you need an extra push, both DigitalOcean and Meilisearch are sending gifts to the contributors.  
DigitalOcean is going to give a T-shirt and a swag pack to the first 55,000 participants of Hacktoberfest.  
Meilisearch will send reusable insulated water bottles to all those who successfully participated in Hacktoberfest and contributed to the [open-source projects](https://github.com/search?q=topic%3Ahacktoberfest+org%3Ameilisearch&type=Repositories) of Meilisearch (look for the repositories with the _hacktoberfest_ topic).  
  
We are also setting **shared goals** that all Meilisearch contributors can help to reach. These goals will unlock perks that will **benefit everyone**.  
We still have to define those perks and will update this blog post accordingly. Some of our ideas so far:

*   financial support to other open-source projects
*   supporting organizations with an environmental impact (like restoration of forests or ocean cleaning)
*   sponsoring organizations promoting diversity in software (like [Black Girls Code](https://wearebgc.org/)).

We would be happy to [hear your ideas](https://discord.gg/meilisearch)!

What happened last year at Meilisearch?
---------------------------------------

Last year, Meilisearch took part in Hacktoberfest [for the first time](/blog/hacktoberfest-with-meilisearch/)e encouraged contributions to the [core Meilisearch repository](https://github.com/meilisearch/MeiliSearch) and to most of the tools we maintain: API wrappers, framework plugins, SDKs...

![](/blog/content/images/2021/09/all-sdk-s.svg)

Started from the bottom...

It was a real success: we merged over fifty contributors’ pull requests. It was twice more than in September 2020.

This year at Meilisearch
------------------------

With around thirty pull requests from external contributors merged in September 2021, we expect more contributions at this year’s Hacktoberfest.

![](/blog/content/images/2021/09/Group-81.svg)

... now we're here.

We’ve made [more repositories available](https://github.com/search?q=topic%3Ahacktoberfest+org%3Ameilisearch&type=Repositories) for Hacktoberfest:

*   our [documentation repository](https://github.com/meilisearch/documentation)
*   the new tools that we’ve created: the [Dart SDK](https://github.com/meilisearch/meilisearch-dart), the [Ruby on Rails](https://github.com/meilisearch/meilisearch-rails) and [Angular](https://github.com/meilisearch/meilisearch-angular) integrations,  the [Gatsby](https://github.com/meilisearch/gatsby-plugin-meilisearch) and [Strapi](https://github.com/meilisearch/strapi-plugin-meilisearch) plugins

How can we help you?
--------------------

Contributing for the first time to an open-source project can be intimidating. That’s why we are happy to guide you step by step through this process. We have several [good first issues](https://github.com/search?q=meilisearch+label%3Ahacktoberfest+state%3Aopen+is%3Aissue&type=Issues) that can help you get started.

Feel free to ask any questions on the GitHub issues of [the corresponding repository](https://github.com/search?q=topic%3Ahacktoberfest+org%3Ameilisearch&type=Repositories), [GitHub Discussions](https://github.com/meilisearch/meilisearch/discussions), or on our [Slack workspace](https://slack.meilisearch.com/) (the [#hacktoberfest](https://meilicommunity.slack.com/archives/C02G1H43J2X) channel is the place to go, but you can also send direct messages to the Meilisearch team members).

We can’t wait to see your next commits 🚀

Contribute to Open Source during Hacktoberfest 2021

If you haven't heard it yet, [Meilisearch v0.22](/blog/whats-new-in-v0-22/)s out, and it comes with a highly requested new feature: sorting at search time.

Search-time sorting is when results are sorted according to parameters decided at query time. By default, Meilisearch orders results according to their [relevancy](https://www.meilisearch.com/docs/learn/core_concepts/relevancy), but you can configure it to let users decide at search time what results they want to see first.

Let me show you how powerful this feature is. If I wanted to search for a MacBook and sort the results by ascending price, I would send the following query:

```json
curl \
  -X POST 'http://localhost:7700/indexes/computers/search' \
  --data '{
    "q": "MacBook",
    "sort": [
        "price:asc"
    ]
}'

```

I could do the opposite and search by descending price. I would just need to replace `asc` by `desc` in my request.

The old way
-----------

Before Meilisearch v0.22, you could only sort search results using the [custom ranking rules](https://www.meilisearch.com/docs/learn/core_concepts/relevancy#custom-rules).

Thanks to the custom ranking rules, we could have our search results sorted by the numeric attribute of our choice. However, the sorting was not at search time, the sorting order was decided in our index settings.

To change the sort order of the search results in the user interface, we had to duplicate the index and set different custom ranking rules for each index.

That's what I did for our [MoMA demo](https://moma.meilisearch.com/) a few months ago. For those who missed it, the MoMA demo is a Meilisearch demo created with the artworks dataset of the [Museum of Modern Art](https://www.moma.org/) available in their [GitHub repository](https://github.com/MuseumofModernArt/collection). You can learn more about the demo in [this blog post](/blog/demo-moma/) wanted the users to be able to sort the artworks by date, so I had to create three indexes:

\-  `artWorks` with the default built-in ranking rules  

\- `artWorksAsc` with a custom ranking rule for ascending sort

\- `artWorksDesc` with a custom ranking rule for descending sort

```javascript
// Get or create indexes
const artWorksIndex = await client.getOrCreateIndex('artWorks', { primaryKey: 'ObjectID' })
const artWorksAscIndex = await client.getOrCreateIndex('artWorksAsc', { primaryKey: 'ObjectID' })
const artWorksDescIndex = await client.getOrCreateIndex('artWorksDesc', { primaryKey: 'ObjectID' })

const defaultRankingRules = [
  'typo',
  'words',
  'proximity',
  'attribute',
  'exactness'
] 

const rankingRulesAsc = [
  'typo',
  'words',
  'proximity',
  'attribute',
  'exactness',
  'asc(DateToSortBy)' // ascending sort
]
const rankingRulesDesc = [
  'typo',
  'words',
  'proximity',
  'attribute',
  'exactness',
  'desc(DateToSortBy)' // descending sort
]

```

The duplication, or triplication, gave the impression of sorting at search time as Meilisearch is blazingly fast.

At that time, sorting was on our [roadmap](https://roadmap.meilisearch.com/), in the Under Consideration tab, and it was one of the most voted features (86 votes).

> We have a [public roadmap](https://roadmap.meilisearch.com/) where you can submit feature or integration ideas and vote for the existing ones.

With the new v0.22 sort feature
-------------------------------

Today, it's a reality. And I've updated the demo to integrate this feature. Let's go through what has changed.

### Behind the scenes

First of all, I have added the following line to the settings:

```javascript
sortableAttributes: ['DateToSortBy']

```

This addition is necessary because we need to inform Meilisearch of the attributes we want to use for sorting.

We only need one index (not three) and the default ranking rules. This has considerably reduced the back-end code. You can change the position of the `sort` rule to tune the relevancy of the search results according to your needs. By default, the `sort` rule in 5th position of the ranking rules to promote results relevant to the user's search.

You can learn more about the ranking rules and how they affect relevancy [here](https://www.meilisearch.com/docs/learn/core_concepts/relevancy).

And if you are curious about why the `sort` rule is in 5th position by default, you can check [this GitHub issue](https://github.com/meilisearch/MeiliSearch/issues/1680#issuecomment-915789791) where our Product Manager explains this choice.

With these modifications, the big block of code above has been reduced to the following line:

```javascript
// Get or create the index
const index = await client.getOrCreateIndex('artWorks', { primaryKey: 'ObjectID' })

```

Easy, right? But, what about the front end?

### In the spotlight

For this demo I used [Vue InstantSearch](https://github.com/algolia/vue-instantsearch/), combined with [Instant Meilisearch](https://github.com/meilisearch/meilisearch-js-plugins/tree/main/packages/instant-meilisearch). This connects the Meilisearch instance with the open-source [InstantSearch](https://github.com/algolia/instantsearch.js) front-end tools allowing us to customize the search environment effortlessly.

The previous code looked like this:

```javascript
<ais-sort-by
:items="[
  { value: 'artWorks', label: 'Featured' },
  { value: 'artWorksAsc', label: 'Date asc.' },
  { value: 'artWorksDesc', label: 'Date desc.' }                    
]"
:class-names="{
    'ais-SortBy': 'MyCustomSortBy'
}"
/>

```

I just needed to transform it into this:

```javascript
<ais-sort-by
:items="[
  { value: 'artWorks', label: 'Featured' },
  { value: 'artWorks:DateToSortBy:asc', label: 'Date asc.' },
  { value: 'artWorks:DateToSortBy:desc', label: 'Date desc.' }                    
]"
:class-names="{
  'ais-SortBy': 'MyCustomSortBy'
}"
/>

```

As you can see, instead of using 3 different indexes (`artWorks`, `artWorksAsc`, and `artworksDesc`), we only need to append the attribute's name to the `artWorks` index followed by the desired sort order, `asc` or `desc`.

```javascript
'artWorks:DateToSortBy:asc'
'artWorks:DateToSortBy:desc'

```

And this is it. Smooth and simple. You can test it [here](https://moma.meilisearch.com/).

![](https://unable-actionable-car.media.strapiapp.com/sortby_a3723cbe47.gif)

Web interface with the query "Magritte" sorting by ascending and then descending date gif

The end-user may not notice the difference, but resource-wise it's much more efficient.

Another great advantage of v0.22 is the new indexer. It's way faster than before, so if you're still using an older version of Meilisearch, I strongly encourage you to [upgrade it](https://www.meilisearch.com/docs/learn/update_and_migration/updating).

The demo source code is available on [GitHub](https://github.com/meilisearch/demos/tree/main/src/MoMA). I invite you to play with it, you can add other attributes to sort by, as long as they are strings or numeric values. For a more in-depth explanation of sorting, take a look at the [dedicated section](https://www.meilisearch.com/docs/learn/getting_started/filtering_and_sorting#sorting) of the documentation.

* * *

_Picture by [Héctor J. Rivas](https://unsplash.com/@hjrc33) on [Unsplash](https://unsplash.com/)_

The art of sorting

After the full rewrite of the core engine required by v0.21, we are finally back on track with our monthly release schedule. You can [read the full changelog](https://github.com/meilisearch/MeiliSearch/releases/tag/v0.22.0), but let's take a look at some of the new version's main changes.

New feature: sorting at search time
-----------------------------------

Though Meilisearch already allowed developers to influence the sorting process by creating custom ranking rules, this was something done during index configuration and applied to all searches in that index. Allowing users to change sorting order and parameters, also known as sorting at search time, was a cumbersome task that required plenty of workarounds like creating several indexes with slightly different ranking rules.

With the introduction of the `sortableAttributes` index setting, [the `sort` search parameter](https://www.meilisearch.com/docs/reference/api/search#sort) and [the `"sort"` ranking rule](https://www.meilisearch.com/docs/learn/core_concepts/relevancy#5-sort), users can now sort results by document field values in ascending or descending order at search time.

To sort at search time, you must first update the `[sortableAttributes](https://www.meilisearch.com/docs/reference/api/settings#sortable-attributes)` index setting. We currently support attributes containing strings and numbers:

```javascript
$ curl \
	-X POST 'http://localhost:7700/indexes/books/settings/sortable-attributes' \
	--data '[
			"price",
			"author"
	]'

```

Once `sortableAttributes` has been configured, you can use the `sort` search parameter to sort results at search time. `[sort](https://www.meilisearch.com/docs/reference/api/search#sort)` requires a list of attributes given in the `attribute:sorting_order` format:

```javascript
$ curl \
  -X POST 'http://localhost:7700/indexes/books/search' \
  --data '{
    "q": "science fiction",
    "sort": [
      "price:asc"
    ]
  }'

```

[For more information on sorting, take a look at our dedicated guide.](https://www.meilisearch.com/docs/learn/advanced/sorting)

Breaking change: custom ranking rules
-------------------------------------

We have aligned the syntax for custom ranking rules and `sort`:

```javascript
# current syntax
"price:asc"

# old syntax
"asc(price)"

```

Custom ranking rules are still the best way of promoting specific types of documents on every search, like when you want to make sure discounted products always feature in a webshop's top search results.

New indexer
-----------

Our second major change on v0.22 should actually be quite invisible. We have refactored our indexer, solving many long-standing issues regarding crashes due to memory overconsumption.

**The transition to the new indexer should be completely seamless and require no change on your side.** Barring any hidden bugs, the only thing you should notice is that indexation is faster and that crashes have become much, much more rare. If you want to know more about indexation and performance, we have added [a new article to our documentation](https://www.meilisearch.com/docs/learn/advanced/indexing#improving-indexing-performance).

In case you still experience issues during indexation, let us know (and [check the FAQ for some of our recommended fixes](https://www.meilisearch.com/docs/faq))!

Other changes
-------------

*   We no longer use Sentry to collect usage data from instances
*   Custom ranking rules now work on strings as well as numbers
*   The default installation script available at [https://install.meilisearch.com](https://install.meilisearch.com) now works with Windows machines using [Cygwin](https://cygwin.com/) or an equivalent environment

Contributors
------------

We wouldn't have gotten here without the support from our community. You're really, truly great and we can't thank you enough for all the effort, suggestions, comments and time you dedicate to Meilisearch. This month, we want to send a special thank you to [@sanders41](https://github.com/sanders41), [@bb,](https://github.com/bb) and [@shekirin](https://github.com/shekhirin).

* * *

And that's all for v0.22! Remember to check out the [changelog for the full release](https://github.com/meilisearch/MeiliSearch/releases/tag/v0.22.0) notes and see you again next month!

What's new in v0.22

Today marks the launch of Meilisearch v0.21, our first new release since March 2021. As you might expect, this one packs a whole lot of changes to our search engine, both big and small. You can check our [exhaustive changelog outlining all breaking changes and download the binaries here](https://github.com/meilisearch/MeiliSearch/releases/tag/v0.21.0), but in this post we wanted to take a closer look at some of the most important updates.

Search performance
------------------

First, one of the best news we could give you: v0.21 is the fastest Meilisearch release (so far). How fast? Our tests using a 1GB dataset with 115 million documents indicate that complex queries return results up to ten times faster than v0.20; filtering those results, previously a slow operation, takes a maximum of 50ms.

Refactor
--------

Clémentine already wrote about [why we chose to refactor](/blog/refactoring-meilisearch/)undamental parts of our core engine, but in case you missed it: it became increasingly hard for us to keep our code easy to read for external contributors and to add new features without negatively impacting performance.

We are very proud of what we accomplished in these months, not only because we managed to greatly improve Meilisearch's performance, but also because we know our search engine has a new, rock-solid foundation.

Facets and filters
------------------

Some of the biggest visible (and breaking) changes in v0.21 concern facets and filters.

First of all, [the search parameters `filters` and `facetFilters` have been replaced by `filter`](https://docs.meilisearch.com/reference/features/search_parameters.html#filter). This new parameter allows you to refine search results based on document attributes whose values are either numbers or strings.

```javascript
$ curl 'http://localhost:7700/indexes/movies/search' \
--data '{ "q": "thriller", "filter": ["genres = Horror", "genres = Mystery"]}'
```

In this example, we create a filter that only returns movies classified as both horror and mystery.

To use an attribute with the `filter` search parameter, you must first add it to [the new `filterableAttributes` index setting](https://docs.meilisearch.com/reference/api/filterable_attributes.html). `filterableAttributes` works exactly like and replaces the `attributesForFaceting` index setting.

```javascript
$ curl \
  -X POST 'http://localhost:7700/indexes/movies/settings' \
  --data '{
      "filterableAttributes": [
          "director",
          "genres"
      ]
  }'

```

Meilisearch no longer distinguishes between facets and filters: you can use the new `filter` search parameter and the `filterableAttributes` index setting to create [faceted search interfaces](https://docs.meilisearch.com/reference/features/filtering_and_faceted_search.html).

Phrase search
-------------

Meilisearch v0.21 supports [phrase searches](https://docs.meilisearch.com/reference/features/configuration.html#disable-analytics). If you enclose one or more search terms in double quotes (for example, `“african-american poet”` or `“John Waters”`), Meilisearch will only return documents that contain those terms exactly as they were written and in the order they were given. Phrase searches are a great way to make a query more precise and come in handy when you know your search should only get one result, such as when looking for a book using its ISBN number.

```javascript
$ curl 'http://localhost:7700/indexes/movies/search' \
  --data '{ "q": "\"John\" Waters" }'
```

Web interface
-------------

In case you didn't know, [Meilisearch automatically creates a web interface](https://docs.meilisearch.com/reference/features/web_interface.html) when you launch an instance in development mode so you can test our search engine right away. We have updated this interface so it's even easier to use (and nicer to look at)!

![](https://unable-actionable-car.media.strapiapp.com/trumen_fast_eba051545b.gif)

New telemetry page and simpler analytics settings
-------------------------------------------------

By default, Meilisearch collects anonymized data from all instances using our search engine. We have made it easier to [disable this behavior](https://docs.meilisearch.com/reference/features/configuration.html#disable-analytics) and [added a new page to our docs explaining exactly what data we collect and how we use it](https://docs.meilisearch.com/learn/what_is_meilisearch/telemetry.html). Privacy is an important issue for us, so please feel free to share any comments, concerns or suggestions you may have.

```javascript
$ ./meilisearch --no-analytics=true
```

Highlight matches in array and object fields
--------------------------------------------

Meilisearch v0.20 allowed you to [highlight matched search terms in string fields](https://docs.meilisearch.com/reference/features/search_parameters.html#attributes-to-highlight) so users could see where exactly a term was found within a document. In v0.21, we have extended this functionality to work with arrays of strings and nested objects. Like before, you can find the highlighted matches inside the `_formatted` object of each returned document.

```javascript
$ curl 'http://localhost:7700/indexes/movies/search' \
  --data '{ 
		"q": "adventure", 
    	"attributesToHighlight": ["title", "genres"] 
	}'
```

```javascript
{
  "id": "50393",
  "title": "The Adventures of Huck Finn",
  "overview": "Climb aboard for an extraordinary version of Mark Twain's sweeping adventure when Walt Disney presents The Adventures of Huck Finn, starring Elijah Wood.",
  "release_date": 733712400,
  "genres": ["Adventure","Family"]
  "_formatted": {
      "id": "50393",
      "title": "The <em>Adventures</em> of Huck Finn",
      "overview": "Climb aboard for an extraordinary version of Mark Twain's sweeping adventure when Walt Disney presents The Adventures of Huck Finn, starring Elijah Wood.",
      "release_date": 733712400,
      "genres": ["<em>Adventure</em>","Family"]
  }
}
```

Title and genre highlighted matches are available inside `_formatted`.

Other changes
-------------

*   You might notice minor performance improvements in the indexer: this is a work-in-progress and we are eager to have your feedback on it
*   The `wordsPosition` [ranking rule](https://docs.meilisearch.com/learn/core_concepts/relevancy.html#ranking-rules) has been merged into `attribute`
*   `max-mdb-size` has been renamed to `[max-index-size](https://docs.meilisearch.com/reference/features/configuration.html#max-index-size)`
*   It is now possible to specify `[max-index-size](https://docs.meilisearch.com/reference/features/configuration.html#max-index-size)` and `[http-payload-limit-size](https://docs.meilisearch.com/reference/features/configuration.html#payload-limit-size)` using human-readable units such as `Kb` or `Gb`
*   We have removed the limit of 200 indexes per instance

Bug fixes
---------

*   Windows instances no longer immediately occupy the maximum index size on launch
*   The [ranking rule](https://docs.meilisearch.com/learn/core_concepts/relevancy.html#ranking-rules) `Words` now works as expected
*   [Dumps](https://docs.meilisearch.com/reference/features/dumps.html) now export all document fields correctly, regardless of whether they are present in `displayedAttributes`

Contributors
------------

A lot of this was made possible thanks to our community: we are honestly humbled by your generosity. Meilisearch is a better search engine because of you.

We want to send a special shout out to [@sanders41](https://github.com/sanders41) and [@bb](https://github.com/bb): your bug reports and feedback were super helpful!

Finally, a big thank you to [@shekhirin](https://github.com/shekhirin) for all the help with the new search engine implementation.

* * *

That's about it for this release! To have a full overview of all changes, breaking and otherwise, you can [check out our changelog](https://github.com/meilisearch/MeiliSearch/releases/tag/v0.21.0).

What’s new in v0.21

Today we are releasing the first release candidate (RC) of Meilisearch v0.21. This is the initial step towards the next version of Meilisearch, and a pretty important one given that it will be our first major release since March.

A big part of v0.21 will be relatively invisible to most end-users: our core team has been hard at work refactoring Meilisearch’s engine, something that is as time-consuming as it is crucial for the long-term health of our codebase. In this post, I want to go over why we decided to refactor Meilisearch, how that impacted our product, and where we’ll go from here.

We won’t be discussing everything that’s changed between v0.20 and v0.21—that’s for another blog post—but we will touch on several of the new features we are most excited about.

Why was refactoring needed?
===========================

We first realized that something was wrong when it became increasingly difficult for our core team to add new features without impacting performance. We could see our code was becoming more difficult to maintain, which is something particularly concerning for an open-source project: our community is our greatest ally and keeping code clean, readable, and pleasant-to-use is crucial if we want to keep our allies happy. We were clearly reaching the limits of what the previous codebase could offer us in terms of performance and ease-of-use, so we decided it was time for a change.

How did we do?
==============

We have a lot of good news—but, as with any major software release, there were some goals we weren’t able to attain.

### Search relevancy

The v0.21.0 will provide new ways to make your search more relevant:

*   You can now use numeric attributes as facets—think things like the price of a product or the release date of a book
*   This was actually requested by our users: the equivalent of Algolia’s `words` criterion [is now available](https://www.meilisearch.com/docs/learn/core_concepts/relevancy#1-words) in Meilisearch!
*   Phrase search: users can now force the engine to only return exact matches by enclosing query terms in double quotes (`"`)
*   Highlighting is now available for array and object values

### Search performance

Searching through huge datasets with Meilisearch has never been so fast! With a 1GB dataset containing around 115 million documents:

*   Queries that return many results are more than ten times faster: searching for a single letter takes less than 50ms in v0.21, compared with 2 seconds in v0.20
*   Similar speed gains when filtering on numbers: most searches take less than 50ms in v0.21

### Indexation

TLDR; indexation is now faster in most cases, but there are exceptions. Lots of room for improvement!

First, the good bits: indexation is globally faster with the refactored search engine.

Unfortunately, we noticed a loss of performance when parsing datasets with lengthy description values (think a list of blog posts or scientific articles with excerpts and abstracts) in v0.21. This is not a complete surprise: the new search engine requires more calculations, which means indexation might take more time. This is not ideal, but we would rather release something that’s not completely optimized than delay v0.21 and all the new features it will introduce. Rest assured, we are doing our best to improve indexation performance.

Another bit of bad news: while we have made significant steps in the right direction and reduced memory consumption across the board, the issue of Meilisearch sometimes crashing due to excessive memory usage has still not been fixed. This is another priority for us going forward.

### **Are there any breaking changes**?

There are indeed! We did our best to avoid breaking changes, but that’s not always possible when we want to keep improving things and making our API easier to use. The two biggest changes related to v.021’s refactoring are:

*   The parameters `filters` and `facetFilter` have been replaced by `filter`. Having two parameters doing almost the same thing added unnecessary complexity when filtering query results
*   Several naming changes that we believe make using Meilisearch more intuitive. None of these have any impact on the end-user experience. A full list will be available when we officially release v0.21

What’s next?
============

Once v0.21 is officially released some time within the next three months, we will return to our monthly release cycle. We are particularly looking forward to working on `sortBy` and geographical search—two features that are highly requested by our users. We hear you loud and clear!

If you are curious about Meilisearch’s upcoming version, feel free to test it and give us as much feedback as possible—we depend on you to catch as many remaining bugs as possible. You can [download the release candidate on GitHub](https://github.com/meilisearch/MeiliSearch/releases/tag/v0.21.0rc0).

Also, a word of advice: we do not recommend using this RC in production. We are confident v0.21 RC1 is looking pretty good, but there are still issues that we need to work out before it is ready for the spotlight.

Thank you again, and see you soon for the official v0.21.0 release!

Refactoring Meilisearch: v0.21 has entered the chat

Meilisearch currently maintains more than 50 open-source projects on GitHub. In the last six months alone we merged over 1000 Pull Requests (PRs), 160 of which came from external contributors.

Ensuring the codebase remains stable and that code quality is always top-notch requires us to be very careful when it comes to merging a new PR. As the number of contributions grows, the automation of this process becomes a necessity in order to keep everything simple for the contributors and safe for Meilisearch's codebase.

In this post I will describe why we decided to use [Bors](https://github.com/bors-ng/bors-ng?ref=blog.meilisearch.com), a merge bot for Github pull requests, to create a better environment for both maintainers and contributors.

## Our merging process
During an open-source contribution, any changes must be done on their own separate branch. Afterwards, when the work on this branch is finished, one of our main requirements before merging is that the new branch is up-to-date with the primary branch—called `main` in most of our repositories.

If the PR is not brought up to date with `main`, you could say that most of the work is done, but *most of the work* is not enough for us. Even if all the automated tests pass on the PR itself, they are not guaranteed to pass when merged if the PR branch and `main` are not aligned.

Before using Bors, this meant we often had to ask PR authors to **rebase their branch** if, for instance, a different PR had been merged meanwhile. This made contribution more complex than we wanted, since not everyone is comfortable with Git’s `rebase` command.

### Why rebasing?
At Meilisearch, we believe keeping a clear Git history is really important for two main reasons:
1 It allows everyone to follow all changes made to the project
2 When debugging, a clear history helps identify which commit introduced the issue

The goal of a rebase is to move the commits from a PR branch to right after the last commit on `main`. Therefore, **rebasing keeps your Git history clear and consistent with the order in which you have merged your PRs**.

Rebasing is not the only way to bring a branch up-to-date with the `main` branch: you can also pull the changes from `main` to the PR branch, for instance. The issue with this approach is that the pull would add a merge commit to the PR branch, which would not keep the repository history clear.

Keeping in mind how important it is to maintain a clear commit tree, **rebasing is the only way to guarantee that the work that is going to be merged fits the current work in production**. If the tests pass on an up-to-date branch, they will also pass once merged into `main`, ensuring your production branch will not break.

## Finding the perfect tool
With our rebase requirements in mind, I began my search for the perfect tool. I wanted to be efficient, so I narrowed my scope and only evaluated tools that were:
* **Free and open source:** the tool had to fit the values of Meilisearch and its community
* **Highly rated:** the tool had to be stable and reliable, since any mistakes when handling PRs are bound to have impactful consequences
* **Well documented and easy to set up:** good documentation saves time that we can use improving Meilisearch

Unfortunately, I did not find as many solutions as I expected within this scope.

The first tool I tried was [Shipits](https://github.com/shipitjs/shipit?ref=blog.meilisearch.com), which I discovered thanks to [this article](https://engineering.shopify.com/blogs/engineering/successfully-merging-work-1000-developers?ref=blog.meilisearch.com) on Shopify’s engineering blog. Though Shipits seemed really solid and promising, I felt it was a better fit for complex integration processes instead of open-source projects just trying to keep their Git history clean.

Another tool I tested was [Kodiak](https://github.com/chdsbd/kodiak?ref=blog.meilisearch.com). The set up was really easy, in large part due to their great documentation. It was a good candidate for our use-case, but the automatic merge process is based on labels that we would have to manage, which does not really fit our workflow. For example, our minimum requirement when merging a PR is obtaining the approval of one reviewer; sometimes, though, I want two people reviewing one PR and it is easy to forget to communicate this to Kodiak. The moment it receives the first approval, Kodiak automatically merges the PR because the one-reviewer-requirement has been respected.

Another thing we noticed was that Kodiak does not update the branch originating the PR by rebasing it and instead creates a Git commit by pulling the main branch into the PR branch, which, as we saw, muddles the repository’s history. In the end, Kodiak did not fit our needs, even if its setup and configuration provided a seamless and hassle-free experience!

Contrary to all the other tools I looked into, **[Bors](https://github.com/bors-ng/bors-ng?ref=blog.meilisearch.com)** was built following a unique and powerful principle described by the original Bors creator in [this article](https://graydon2.dreamwidth.org/1597.html?ref=blog.meilisearch.com):

> *The Not Rocket Science Rule Of Software Engineering: automatically maintain a repository of code that always passes all the tests.*

This "rule" perfectly fit our requirements and made Bors our final choice.

## How does Bors work?
Bors is a merge bot—meaning, it is an application that **automates aspects of the PR merging process**. Its setup is straightforward and, like Kodiak, very well documented. Indeed, configuration can be a single `bors.toml` file containing the names of tests we want to execute before merging.

All Bors commands have to be given through comments in a PR. To merge a PR, all we need to do is use `bors merge`.
Bors first applies a rebase before running the tests and, if they succeed, merges them back into `main`. To be more accurate, Bors does not actually rebase the branch of the PR: it merges the commits of the PR into another branch, called `staging`, that is already up-to-date with `main`. If the tests do not pass on `staging`, Bors returns a failure and does not merge the PR.

The icing on the cake: **Bors is also able to manage merging multiple PRs at the same time**, which means we don't need to merge them one by one. Each PR is added to a queue and will be checked with the last version on `main` at regular intervals.

If Bors finds conflicts between the PR and the main branch, it cannot make the decision about which final changes to apply. In this situation, the contributors have to rebase the branch manually—if that happens to you, I wrote this [quick tutorial](https://gist.github.com/curquiza/5f7ce615f85331f083cd467fc4e19398?ref=blog.meilisearch.com) on how to rebase from a forked repository.

## Conclusion: which problems have we solved?
We at Meilisearch have used Bors for a few months now and are really satisfied. We know that keeping the Git history clear while providing a stable codebase can be very complex, but so far Bors has helped us greatly optimize our workflow. With Bors integrated in our workflow there is:
* No need to ask and wait for PR authors to rebase
* No need to test and merge PRs one by one
* No frustration for our contributors: they all do amazing work, but some of them are not really comfortable with Git’s rebase feature, which is indeed not always easy to use—especially when working from a forked repository!

**Bors makes both maintainers and contributors happier**; we can, therefore, recommend it for projects with the same use-case as ours.

Automate pull requests merging with Bors

<Callout>
  This guide is for Strapi v3. If you are using Strapi v4, check [this post](/blog/strapi-v4-plugin-meilisearch/)
</Callout>

As the web evolves, more and more tools are available to take care of complex jobs for us. Why create a CRUD API from scratch when you can generate one in a few clicks? Why struggle with difficult search operations and queries, when simple and efficient solutions exist?

Maybe we're intimidated by new technologies, or concerned about investing time in tools that don't pan out. Or, more likely, _we may not even be aware that a simple solution exists._

![](https://unable-actionable-car.media.strapiapp.com/truemen_d2b99b9b0a.gif)

Meilisearch in action

This tutorial will show you, in the fewest steps possible, how to use Strapi and Meilisearch to create a search-based web-app. First, let's get acquainted with our tools!

Introducing our Tools
---------------------

### Strapi

[Strapi](https://strapi.io/) is a headless CMS. It provides a quick way to create a back-end where we can add and store data. The data is then available through a REST API without having to code anything or configure our database.

### Meilisearch

[Meilisearch](https://www.meilisearch.com/docs/learn/what_is_meilisearch/overview) is a fast, open-source search engine that's easy to use and deploy. The aim of Meilisearch is to create a relevant search experience out of the box in very few steps and with no configuration needed.

Requirements
------------

To be able to follow this tutorial, you'll need the following:

*   An open [terminal or command prompt](https://www.ionos.com/help/email/troubleshooting-mail-basicmail-business/access-the-command-prompt-or-terminal)
*   [Node.js](https://nodejs.org/en/download/) {">= 10.16 and <= 14"}: this makes it possible to run JS outside a browser
    *   You can check the active version with the command `node --version`
    *   If your version of Node is outside this range, we recommend that you [install nvm](https://github.com/nvm-sh/nvm/blob/master/README.md#about) and use it to access Node 14
*   NPM and NPX >= 6.x (installed with Node.js): package managers that help you access and use JS libraries

Steps:
------

1.  [Create a working directory](#create-a-directory-for-our-app)
2.  [Create Strapi Back End](#create-a-back-end-using-strapi)
3.  [Start Meilisearch](#launch-and-start-meilisearch)
4.  [Connect Strapi and Meilisearch](#connect-strapi-and-meilisearch)
5.  [Conclusion](#conclusion)

Create a directory for our app
------------------------------

We don't want our app to be all over the place! Let's create a directory where we will add every part of our application.

```bash
mkdir my-app
cd my-app
```

If you are not using a [UNIX-based operating system](https://www.eukhost.com/blog/webhosting/linux-flavors/) please follow this guide to [create a directory](https://www.computerhope.com/issues/ch000742.htm).

Create a back end using Strapi
------------------------------

In this section we are going to create and run a back-end using Strapi.

Our first step is to generate a Strapi Application. Go to your open terminal window and run the following command:

```bash
npx create-strapi-app@3.5.4 back --quickstart

```
<Callout>
  Using [npx](https://www.npmjs.com/package/npx) we run a specific version of the package without installing it globally. Note that this guide may not work with a different version.
</Callout>

This command creates a Strapi app in a new directory called `back` and opens the admin dashboard. Create an account or log in so that you have access.

![](https://unable-actionable-car.media.strapiapp.com/Screenshot_2021_04_20_at_14_28_54_1_453a624ffa.png)

If you lose this page at any time, just go to `http://localhost:1337/admin` in your browser

Once you have created your account, you should be redirected to Strapi's admin dashboard. This is where we will configure our back-end API.

Our next step is to create a new collection type—in this case, it'll be a collection of restaurants. Complete [step 3 of Strapi's quick start guide](https://strapi.io/documentation/developer-docs/latest/getting-started/quick-start.html#_3-create-a-restaurant-content-type) to continue.

![](https://unable-actionable-car.media.strapiapp.com/Screenshot_2021_04_20_at_15_31_41_2effed8eb3.png)

Admin dashboard landing page

After finishing [step 3 of Strapi's quick start guide](https://strapi.io/documentation/developer-docs/latest/getting-started/quick-start.html#_3-create-a-restaurant-content-type), a new collection named `Restaurants` should have appeared under `Collection Types`. If we click on it, we can see that there are still no restaurants. Let's add some!

![](https://unable-actionable-car.media.strapiapp.com/Screenshot_2021_04_20_at_15_07_36_63c48765e5.png)

`Restaurants` collection landing page

Click on `+ Add New Restaurants` in the upper-right corner of the dashboard. Now let's add three restaurants, one by one:

*   Name: `The Butter Biscotte`. Description:  `All about butter, nothing about health.`
*   Name: `The Slimy Snail` Description: `Gastronomy is made of garlic and butter.`
*   Name: `The Smell of Blue` Description: `Blue Cheese is not expired, it is how you eat it. With a bit of butter and a lot of happiness.`

![](https://unable-actionable-car.media.strapiapp.com/Screenshot_2021_04_20_at_15_15_38_2c431c5150.png)

Create an entry in the Restaurant Collection.

For each restaurant, you need to press `save` and then `publish`. Once the three restaurants have been added, you should end up with the following page:

![](https://unable-actionable-car.media.strapiapp.com/Screenshot_2021_04_20_at_15_22_55_e0137d6c9d.png)

Main page of `Restaurants` showcasing the restaurants we have added

Our Strapi back end is now up and running! Strapi automatically creates a REST API for our `Restaurants` collection. Check out Strapi's documentation for all available [API endpoints](https://strapi.io/documentation/developer-docs/latest/developer-resources/content-api/content-api.html#api-endpoints).

Next, it's time to bring Meilisearch into the mix.

Launch and Start Meilisearch
----------------------------

**tl;dr:** [download, install and start Meilisearch](https://docs.meilisearch.com/learn/getting_started/installation.html#download-and-launch).

Want to avoid a local installation? Use our [Meilisearch cloud](https://cloud.meilisearch.com/) free 14-day trial or our [one-click install on DigitalOcean](https://marketplace.digitalocean.com/apps/meilisearch) and [continue to the next section](#connect-strapi-and-meilisearch).

If you made it this far, you should already have an open terminal window running Strapi. If not or if you closed it by accident, please [follow this guide](https://www.ionos.com/help/email/troubleshooting-mail-basicmail-business/access-the-command-prompt-or-terminal), navigate to the directory `.../my-app/back` that we created, and run the command `npm run develop` to restart Strapi.

Let's take a moment to **open a second terminal window** and move to the `my-app` directory. This window will be used to run Meilisearch.

Inside `my-app`, create a new directory called `meilisearch-binary` .

```bash
mkdir meilisearch-binary
cd meilisearch-binary
```

Create and move to directory where we will run Meilisearch

Execute the following command to download Meilisearch in the current directory. If cURL doesn't work for you, consider trying one of the [many other methods to download and install](https://docs.meilisearch.com/learn/getting_started/installation.html#download-and-launch) Meilisearch.

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

Download and install Meilisearch

We now have the `meilisearch` binary in our directory. Let's run it!

```bash
# Launch Meilisearch
./meilisearch
```

Launch Meilisearch

You should see a big chunk of text (including some ASCII art) confirming that Meilisearch is up and running.

![](https://unable-actionable-car.media.strapiapp.com/MS_adress_75a76c4b2b.png)

Running Meilisearch

Find the line titled `Server listening on`. This lets us know where Meilisearch is being served. Once you've found it, open this adress in your browser.

You should arrive on a web page without much to look at.

![](https://unable-actionable-car.media.strapiapp.com/Screenshot_2021_04_21_at_13_21_44_d9162084ee.png)

The Meilisearch web interface w/ empty index

This is the Meilisearch [web interface](https://www.meilisearch.com/docs/learn/what_is_meilisearch/search_preview). It will remain empty until we add some data to our Meilisearch instance.

Data, you say? It just so happens we already have some in our Strapi app! Time to connect the two and start searching through our data with Meilisearch.

Connect Strapi and Meilisearch
------------------------------

In order to add the Meilisearch plugin to Strapi, we need to quit our Strapi app. Go to the terminal window running Strapi (_make sure it's not the one running Meilisearch!_) and push `control + c` to kill the process.

Once you've done that, move inside the `back` directory and install the plugin.

```json
cd back
npm install strapi-plugin-meilisearch
```

After the installation, we have to rebuild our Strapi app before starting it again in development mode, since it makes configuration easier.

```bash
npm run build
npm run develop
```

At this point, our Strapi app should be running once again on the default address: [`http://localhost:1337/admin/`](http://localhost:1337/admin/) . Visiting it in your browser, you should see an admin sign-in page; enter the same credentials as before.

Once connected, you should see a new `Plugin` on the left side of the screen: Meilisearch! Let's click on it.

![](https://unable-actionable-car.media.strapiapp.com/Screenshot_2021_04_21_at_14_32_44_c00e3d34f8.png)

Arriving on the Meilisearch plugin page, we can see that the information is split into two sections:

*   Meilisearch credentials
*   Strapi collections

![](https://unable-actionable-car.media.strapiapp.com/Screenshot_2021_04_21_at_14_44_12_6b821d2d2e.png)

Meilisearch plugin page of Strapi admin dashboard

First, we need to add the credentials of our Meilisearch instance so that Strapi knows where to send our data.

You may remember from the previous step that Meilisearch runs on `http://localhost:7700` by default. Add this in the `Meilisearch Host` field, then click `Add` to connect your Meilisearch instance to Strapi.  

![](https://unable-actionable-car.media.strapiapp.com/credentials_6fe7804ffa.gif)

Add credentials to Meilisearch.

> Note that we leave `Meilisearch Api Key` blank because we started Meilisearch without a [master key](https://www.meilisearch.com/docs/learn/configuration/instance_options#master-key).

Great! Now it's time to add your Strapi collection to Meilisearch.

Try clicking on the check box next to `restaurant` and watch as Meilisearch instantly begins processing your data. Because we only have three documents, the indexing time is practically non-existent.

![](https://unable-actionable-car.media.strapiapp.com/Large_GIF_956x212_5f52b4fd0f.gif)

Add restaurants to Meilisearch

We can now go back to our Meilisearch host address: `http://localhost:7700`. After refreshing, you should observe that the page is not as empty as before.

![](https://unable-actionable-car.media.strapiapp.com/Screenshot_2021_04_22_at_10_07_08_6dbd424e4d.png)

Demo page of Meilisearch

We did it! Try inputting "butter" and check out the results.

#### Front-end Interface

Using [instant-meilisearch](https://github.com/meilisearch/meilisearch-js-plugins/tree/main/packages/instant-meilisearch), you can implement a front-end search interface in [React](https://github.com/meilisearch/meilisearch-react), [Vue](https://github.com/meilisearch/meilisearch-vue), or [Angular](https://github.com/meilisearch/meilisearch-angular) in no time at all.  
  
Here's an interactive [code sandbox](https://codesandbox.io/s/react-movies-demo-e1dqh) (in React) where you can get a feel for the different components. You can't break anything, so feel free to play around!

### Conclusion

I hope this article was a pleasant introduction to the new [Meilisearch plugin for Strapi](https://github.com/meilisearch/strapi-plugin-meilisearch). However, this is just the beginning!

If you have any questions, please join us [on Discord](https://discord.gg/meilisearch). If you like Meilisearch, [a star on GitHub means a lot](https://github.com/meilisearch/meilisearch). For more information, see our:

*   [Documentation](https://www.meilisearch.com/docs/)
*   [GitHub](https://github.com/meilisearch/meilisearch)
*   [Strapi Plugin](https://github.com/meilisearch/strapi-plugin-meilisearch)
*   [Discord](https://discord.gg/meilisearch)

Meilisearch latest news and company updates