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    0.2.7 • Public • Published



    A LoopBack microservice used for searching over configured models. It uses in-build Full Text Search support in PostgreSQL and MySQL databases to perform searches.


    npm i @sourceloop/search-service


    • Create a new Loopback4 Application (If you don't have one already) lb4 testapp
    • Install the search service npm i @sourceloop/search-service
    • Bind the configuration for the service to the SearchServiceBindings.Config key -
          useCustomSequence: false, //default
          type: SearchResult, //default
          models: [ //required
              ToDo, //according to project
                  model: User,
                  columns: {
                      name: 'username',
                      description: 'about'
          controller: { //optional
              name: 'ToDo',
              basePath: '/todo/search',
              authorizations: ['SearchTodo']
    • Add the SearchService to your Loopback4 Application (in application.ts).
      // import the SearchServiceComponent
      import {SearchServiceComponent} from '@sourceloop/search-service';
       // add Component for SearchServiceComponent
    • Set up a Loopback4 Datasource with dataSourceName property set to SearchServiceBindings.DATABASE_NAME. You can see an example datasource here. This service supports MySQL and PostgreSQL based datasources as of now.
    • Start the application npm start



    The service comes with a default sequence with inbuilt authentication and authorization using the loopback4-authentication and loopback4-authorization. If you want to use your custom sequence instead, set this option as true.


    Type of the result set, by default it is a model with two properties - name and description;


    It sets the models and columns over which the search is performed. It's value is a list with two types of values -

    • Models - A class that extends the Loopback Model.
    • An Object with two properties -
      • model - A class that extends the Loopback Model
      • columns - A key-value map that maps the keys of the database model to the keys in the result set.


    Configuration for the controller, it accepts three properties -

    • name - name of the Controller, by default it is SearchController
    • basePath - basePath of the controller, be default it is {name}/search, if even the name is not provided, it is just /search
    • authentication - if authentication should be required or not, this must be enable to use authorizations
    • authorizations - list of string corresponding to the permissions required for the search API, by default equal to ['*'](allowed for everyone).
    • recents - provider an endpoint to fetch recent searches. authentication must be enabled to use this.
    • recentCount - number of recent searches to be saved for each user, default value is 5.

    Setting up a DataSource

    Here is a Sample Implementation DataSource implementation using environment variables.

    import {inject, lifeCycleObserver, LifeCycleObserver} from  '@loopback/core';
    import {juggler} from  '@loopback/repository';
    import {SearchServiceBindings.DATABASE_NAME} from  '@sourceloop/search-service';  
    const  config = {
      name:  SearchServiceBindings.DATABASE_NAME,
      connector:  'postgresql',
      url:  '',
      host:  process.env.DB_HOST,
      port:  process.env.DB_PORT,
      user:  process.env.DB_USER,
      password:  process.env.DB_PASSWORD,
      database:  process.env.DB_DATABASE,
      schema:  process.env.DB_SCHEMA,
    export  class  SearchDbDataSource  extends  juggler.DataSource implements  LifeCycleObserver {
      static  dataSourceName = SearchServiceBindings.DATABASE_NAME;
      static  readonly  defaultConfig = config;
        // You need to set datasource configuration name as '' otherwise you might get Errors
        @inject('', {optional:  true})
        dsConfig: object = config,
      ) {

    Also if you are using postgres datasource, you need to add the following function in your db -

    CREATE OR REPLACE FUNCTION f_concat_ws(text, VARIADIC text[])
      RETURNS text LANGUAGE sql IMMUTABLE AS 'SELECT array_to_string($2, $1)';

    And to improve performance define an index like this -

    CREATE INDEX tbl_fts_idx ON main.<TABLENAME> USING GIN (
           to_tsvector('english', f_concat_ws(' ', <COLUMN1>, <COLUMN2>)));

    API Documentation

    Common Headers

    Authorization: Bearer where is a JWT token signed using JWT issuer and secret. Content-Type: application/json in the response and in request if the API method is NOT GET

    Common Request path Parameters

    {version}: Defines the API Version

    Common Responses

    200: Successful Response. Response body varies w.r.t API 401: Unauthorized: The JWT token is missing or invalid 403: Forbidden : Not allowed to execute the concerned API 404: Entity Not Found 400: Bad Request (Error message varies w.r.t API) 201: No content: Empty Response


    npm i @sourceloop/search-service

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