Semantic search is an advanced data searching technique that enhances the accuracy and relevance of search results by understanding the contextual meaning and intent behind user queries.
Full-text search has always been a challenge with firebase because Cloud Firestore doesn’t support native indexing or search for text fields in documents. Additionally, downloading an entire collection to search for fields client-side isn’t practical. Therefore, to enable full text search of your Cloud Firestore data, we have to use a dedicated third-party search service.
MeiliSearch is a RESTful search API. It aims to be a ready-to-go solution for everyone who wants a fast and relevant search experience for their end-users.
All of MeiliSearch’s features are provided right out of the box, and can be easily configured.
Run MeiliSearch There are many easy ways to download and run a MeiliSearch instance.
For example, if you use Docker:
docker pull getmeili/meilisearch:latest
docker run -it --rm -p 7700:7700 getmeili/meilisearch:latest ./meilisearch --master-key=masterKey
NB: you can also download MeiliSearch from Homebrew or APT.
Adding records with Cloud Functions With npm:
npm install meilisearch
Cloud functionsindex.js:
const functions = require("firebase-functions");
const { MeiliSearch } = require('meilisearch');
const admin = require('firebase-admin');
admin.initializeApp();
const client = new MeiliSearch({
host: '<http://127.0.0.1:7700>',
apiKey: 'masterKey',
});
// Add the search index every time a secret post is written.
exports.onCreateSecret = functions.firestore.document('secrets/{id}')
.onCreate((snap, context) => {
// Create a document
const documents = [
{
id: snapshot.id,
secret: snapshot.data().secret,
authorName: snapshot.data().authorName,
authorUid: snapshot.data().authorUid,
timestamp: new Date(timestamp.seconds*1000).toLocaleDateString()
}
];
// Write to the meilisearch index
let response = await client.index('secrets').addDocuments(documents);
console.log(response); // => { "updateId": 0 }
});
You can install the meilisearch package by adding a few lines into pubspec.yaml file.
meilisearch | Dart Package
Searching for records
// a function to search with meilisearch
Future<void> searchSecrets(String _query) async {
try {
var client = MeiliSearchClient('<http://127.0.0.1:7700>', 'masterKey');
var index = client.index('secrets');
var results = await index.search(_query);
if (results.hits!.length == 0) {
print('No results found');
}else{
print(results.hits);
}
} catch (e) {
print('Error: $e');
}
}
Since meilisearch is self-hosted, This gives you the freedom of control. Meilisearch can be deployed anywhere of your choice (docker-containers).
Here is a guide on how to deploy.
For my project, i used Qovery which offered a free plan at $0.
Qovery is a platform that combines the power of Kubernetes, the reliability of AWS, and the simplicity of Heroku to deploy your applications in the Cloud.
In conclusion, this approach not only resolves the challenges posed by traditional Firebase searches but also empowers developers to maintain control over their data infrastructure.
As demonstrated, semantic search stands out as an affordable and effective solution for implementing full-text search among others, thereby enriching the user experience in applications. This case study serves as a valuable reference for developers seeking to implement similar functionalities in their projects, highlighting the potential of combining innovative technologies to meet user needs effectively.