Adding Tweet Streaming Feature in World Mood Tracker loklak App

The World Mood Tracker was added to loklak apps with the feature to display aggregated data from the emotion classifier of loklak server. The next step in the app was adding the feature to display the stream of Tweets from a country as they are discovered by loklak. With the addition of stream servlet in loklak, it was possible to utilise it in this app.

In this blog post, I will be discussing the steps taken while adding to introduce this feature in World Mood Tracker app.

Props for WorldMap component

The WorldMap component holds the view for the map displayed in the app. This is where API calls to classifier endpoint are made and results are displayed on the map. In order to display tweets on clicking a country, we need to define react props so that methods from higher level components can be called.

In order to enable props, we need to change the constructor for the component –

export default class WorldMap extends React.Component {
    constructor(props) {


We can now pass the method from parent component to enable streaming and other components can close the stream by using props in them –

export default class WorldMoodTracker extends React.Component {
    showStream(countryName, countryCode) {
        /* Do something to enable streaming component */
    render() {
        return (
                <WorldMap showStream={this.showStream}/>


Defining Actions on Clicking Country Map

As mentioned in an earlier blog post, World Mood Tracker uses Datamaps to visualize data on a map. In order to trigger a piece of code on clicking a country, we can use the “done” method of the Datamaps instance. This is where we use the props passed earlier –

done: function(datamap) {
    datamap.svg.selectAll('.datamaps-subunit').on('click', function (geography) {
        props.showStream(, reverseCountryCode(;


The name and ID for the country will be used to display name and make API call to stream endpoint respectively.

The StreamOverlay Component

The StreamOverlay components hold all the utilities to display the stream of Tweets from loklak. This component is used from its parent components whose state holds info about displaying this component –

export default class WorldMoodTracker extends React.Component {
    getStreamOverlay() {
        if (this.state.enabled) {
            return (<StreamOverlay
                show={true} channel={}
                country={} onClose={this.onOverlayClose}/>);

    render() {
        return (


The corresponding props passed are used to render the component and connect to the stream from loklak server.

Creating Overlay Modal

On clicking the map, an overlay is shown. To display this overlay, react-overlays is used. The Modal component offered by the packages provides a very simple interface to define the design and interface of the component, including style, onclose hook, etc.

import {Modal} from 'react-overlays';

<Modal aria-labelledby='modal-label'
    <div style={dialogStyle()}>


It must be noted that modalStyle and backdropStyle are React style objects.

Dialog Style

The dialog style is defined to provide some space at the top, clicking where, the overlay is closed. To do this, vertical height units are used –

const dialogStyle = function () {
    return {
        position: 'absolute',
        width: '100%',
        top: '5vh',
        height: '95vh',
        padding: 20


Connecting to loklak Tweet Stream

loklak sends Server Sent Events to clients connected to it. To utilise this stream, we can use the natively supported EventSource object. Event stream is started with the render method of the StreamOverlay component –

render () {


This channel is used to connect to twitter/country/<country-ID> channel on the stream and then this can be passed to EventStream constructor. On receiving a message, a list of Tweets is appended and later rendered in the view –

startEventSource(country) {
    let channel = 'twitter%2Fcountry%2F' + country;
    if (this.eventSource) {
    this.eventSource = new EventSource(host + '/api/stream.json?channel=' + channel);
    this.eventSource.onmessage = (event) => {
        let json = JSON.parse(;
        if (this.state.tweets.length > 250) {


The size of the list is restricted to 250 here, so when a newer Tweet comes in, the oldest one is chopped off. And thanks to fast DOM actions in React, the rendering doesn’t take much time.

Rendering Tweets

The Tweets are displayed as simple cards on which user can click to open it on Twitter in a new tab. It contains basic information about the Tweet – screen name and Tweet text. Images are not rendered as it would make no sense to load them when Tweets are coming at a high rate.

function getTweetHtml(json) {
    return (
        <div style={{padding: '5px', borderRadius: '3px', border: '1px solid black', margin: '10px'}}>
            <a href={} target="_blank">
            <div style={{marginBottom: '5px'}}>
            <div style={{overflowX: 'hidden'}}>{json['text']}</div>


They are rendered using a simple map in the render method of StreamOverlay component –

<div className={styles.container} style={{'height': '100%', 'overflowY': 'auto',
    'overflowX': 'hidden', maxWidth: '100%'}}>


Closing Overlay

With the previous setup in place, we can now see Tweets from the loklak backend as they arrive. But the problem is that we will still be connected to the stream when we click-close the modal. Also, we would need to close the overlay from the parent component in order to stop rendering it.

We can use the onclose method for the Modal here –

close() {
    if (this.eventSource) {
        this.eventSource = null;


Here, props.onClose() disables rendering of StreamOverlay in the parent component.


In this blog post, I explained how the flow of props are used in the World Mood Tracker app to turn on and off the streaming in the overlay defined using react-overlays. This feature shows a basic setup for using the newly introduced stream API in loklak.

The motivation of such application was taken from emojitracker by mroth as mentioned in fossasia/ The changes were proposed in fossasia/ by @singhpratyush (me).

The app can be accessed live at


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Creating Dynamic Forms Using Custom-Form API in Open Event Front-end

In Open Event Front-end allows the the event creators to customise the sessions & speakers forms which are implemented on the Orga server using custom-form API. While event creation the organiser can select the forms fields which will be placed in the speaker & session forms.

In this blog we will see how we created custom forms for sessions & speakers using the custom-form API. Lets see how we did it.

Retrieving all the form fields

Each event has custom form fields which can be enabled on the sessions-speakers page, where the organiser can include/exclude the fields for speakers & session forms which are used by the organiser and speakers.

return this.modelFor('events.view').query('customForms', {});

We pass return the result of the query to the new session route where we will create a form using the forms included in the event.

Creating form using custom form API

The model returns an array of all the fields related to the event, however we need to group them according to the type of the field i.e session & speaker. We use lodash groupBy.

allFields: computed('fields', function() {
  return groupBy(this.get('fields').toArray(), field => field.get('form'));

For session form we run a loop allFields.session which is an array of all the fields related to session form. We check if the field is included and render the field.

{{#each allFields.session as |field|}}
  {{#if field.isIncluded}}
    <div class="field">
      <label class="{{if field.isRequired 'required'}}" for="name">{{}}</label>
      {{#if (or (eq field.type 'text') (eq field.type 'email'))}}
        {{#if field.isLongText}}
          {{widgets/forms/rich-text-editor textareaId=(if field.isRequired (concat 'session_' field.fieldIdentifier '_required'))}}
          {{input type=field.type id=(if field.isRequired (concat 'session_' field.fieldIdentifier '_required'))}}

We also use a unique id for all the fields for form validation. If the field is required we create a unique id as `session_fieldName_required` for which we add a validation in the session-speaker-form component. We also use different components for different types of fields eg. for a long text field we make use of the rich-text-editor component.

Thank you for reading the blog, you can check the source code for the example here.


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Controlling Motors using PSLab Device

PSLab device is capable of building up a complete science lab almost anywhere. While the privilege is mostly taken by high school students and teachers to perform scientific experiments, electronic hobbyists can greatly be influenced from the device. One of the usages is to test and debug sensors and other electronic components before actually using them in their projects. In this blog it will be explained how hobbyist motors are made functional with the use of the PSLab device.

There are four types of motors generally used by hobbyists in their DIY(Do-It-Yourself) projects. They are;

  • DC Gear Motor
  • DC Brushless Motor
  • Servo Motor
  • Stepper Motor

DC motors do not require much of a control as their internal structure is simply a magnet and a shaft which was made rotatable around the magnetic field. The following image from slideshare illustrates the cross section of a motor. These motors require high currents and PSLab device as it is powered from a USB port from a PC or a mobile phone, cannot provide such high current. Hence these type of motors are not recommended to use with the device as there is a very high probability it might burn something.

In the current context, we are concerned about stepper motors and servo motors. They cannot be powered up using direct currents to them. Inside these motors, the structure is different and they require a set of controlled signals to function. The following diagram from electronics-tutorials illustrates the feedback loop inside a servo motor. A servo motor is functional using a PWM wave. Depending on the duty cycle, the rotational angle will be determined. PSLab device is capable of generating four different square waves at any duty cycle varying from 0% to 100%. This gives us freedom to acquire any angle we desire from a servo motor. The experiment “Servo Motors” implement the following method where it accepts four angles.

public void servo4(double angle1, double angle2, double angle3, double angle4)

The experiment supports control of four different servo motors at independant angles. Most of the servos available in the market support only 180 degree rotation where some servos can rotate indefinitely. In such a case, the servo will rotate one cycle and reach its initial position.

The last type of motor is stepper motor. As the name says it, this motor can produce steps. Inside of the motor, there are four coils and and five wires coming out of the motor body connecting these coils. The illustration from Wikipedia shows how four steps are acquired by powering up the respective coil in order. This powering up process needs to be controlled and hard to do manually. Using PSLab device experiment “Stepper Motor”, a user can acquire any number of steps just by entering the step value in the text box. The implementation consists of a set of method calls;

scienceLab.stepForward(steps, 100);

scienceLab.stepBackward(steps, 100);

A delay of 100 milliseconds is provided so that there is enough time to produce a step. Otherwise the shaft will not experience enough resultant force to move and will remain in the same position.

These two experiments are possible with PSLab because the amount of current drawn is quite small which can be delivered through a general USB port. It is worth mentioning that as industry grade servo and stepper motors may draw high current as they were built to interact with heavy loads, they are not suitable for this type of experiments.


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Creating GUI for configuring SUSI Linux Settings

SUSI Linux app provides access to SUSI on Linux distributions on desktop as well as hardware devices like Raspberry Pi. The settings for SUSI Linux are controlled with the use of a config.json file. You may edit the file manually, but to provide safe configurations, we have a config generator script. You may run the script to configure settings like TTS Engine, STT Engine, authentication, choice about the hotword engine etc. Generally, it is easier to configure application settings through a GUI. Thus, we added a GUI for it using PyGTK and Glade.

Glade is a GUI designer for GNOME based Linux systems. I wrote a blog about how to create user interfaces in Glade and access it from Python code in SUSI Linux. Now, for creating UI for Configuration screen, we need to choose an ideal layout. Glade provides various choices like BoxLayout, GridLayout, FlowBox, ListBox , Notebook etc. Since, we need to display only basic settings options, we select the BoxLayout for this purpose.

BoxLayout as the name suggests, forms a box like arrangement for widgets. You can arrange the widgets in either Landscape or Horizontal Layout. We select Application Window as a top-level container and add a BoxLayout container in it. Now, in each box of the BoxLayout, we need to add the widgets like ComboBox and Switch for user’s choice and a Label. This can be done by using a horizontal BoxLayout with corresponding widgets. After arranging the UI in above described manner, we have a GUI like below.

If you see the current window in the preview now, you will find that the ComboBox do not have any items. We need to define items in the ComboBox using a GTKListStore. You may refer to this video tutorial to see how this can be done.

Now, when we see the preview, our GUI is fully functional. We have options for Speech Recognition Service, Text to Speech Service in ComboBox. Other simple settings are available as switches.

Now, we need to add functionality to our UI. We want our code to be modular and structured, therefore, we declare a ConfigurationWindow class. Though the ideal way to handle such cases is inheriting from the Gtk.Window class, but reading the documentation of PyGTK+ 3, I could not find a way to do this for windows created through Glade. Thus, we will use composition for storing the window object. We add window and other widgets present in the UI as properties of ConfigurationWindow class like this.

class ConfigurationWindow:
   def __init__(self) -> None:
       builder = Gtk.Builder()

       self.window = builder.get_object("configuration_window")
       self.stt_combobox = builder.get_object("stt_combobox")
       self.tts_combobox = builder.get_object("tts_combobox")
       self.auth_switch = builder.get_object("auth_switch")
       self.snowboy_switch = builder.get_object("snowboy_switch")
       self.wake_button_switch = builder.get_object("wake_button_switch")

Now, we need to connect the Signals from our configuration window to the Handler. We declare the Handler as a nested class in the ConfigurationWindow class because its scope of usage is inside the ConfigurationWindow object. Then you may connect signals to an object of the Handler class.


Since we may need to modify the state of the widgets, we hold a reference of the parent ConfigurationWindow object in the Handler and pass the self as a parameter to the Handler. You may read more about using the handlers in my previous blog.

In the Handler, we connect to the config.json file and change the parameters of the the file based on the user inputs on the GUI. We handle it for the Text to Speech selection comboBox in the following manner. We also declare two addition Dialogs for handling the input of credentials by the users for the Watson and Bing services.

def on_stt_combobox_changed(self, combo: Gtk.ComboBox):
   selection = combo.get_active()

   if selection == 0:
       config['default_stt'] = 'google'

   elif selection == 1:
       credential_dialog = WatsonCredentialsDialog(self.config_window.window)
       response =

       if response == Gtk.ResponseType.OK:
           username = credential_dialog.username_field.get_text()
           password = credential_dialog.password_field.get_text()
           config['default_stt'] = 'watson'
           config['watson_stt_config']['username'] = username
           config['watson_stt_config']['password'] = password


   elif selection == 2:
       credential_dialog = BingCredentialDialog(self.config_window.window)
       response =

       if response == Gtk.ResponseType.OK:
           api_key = credential_dialog.api_key_field.get_text()
           config['default_stt'] = 'bing'
           config['bing_speech_api_key']['username'] = api_key


Now, we declare two more methods to show and exit the Window.

def show_window(self):

def exit_window(self):

Now, we may use the ConfigurationWindow class object anywhere from our code. This modularized approach is better when you need to manage multiple windows as you can just declare the Window of a particular type and show it whenever need in your code.


  • Glade usage Youtube tutorial:
  • Creating GUI using PyGTK for SUSI Linux:
  • PyGObject Documentation:
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Snackbar for Error Handling in Twitter Followers Insight loklak App

In this blog post am going to explain how the Twitter Followers Insight app handles error which occurs when when no query is passed to the “Search” function i.e., when the search is proceeded with an empty query.

How to handle the Exception

In such cases, I have used SNACKBAR / TOAST. Snackbar / Toast is used to popup an error notification on the screen when an exception occurs.

Script for Snackbar / Toast:

In the below script, initially the error is set to null i.e., no error. The “showError” function is which is being called when there occurs a situation of no query or an empty query. The function below helps to show an error popup which only shows till a time limit.

    $scope.error = null;

    $scope.showError = function() {
        setTimeout(function(){ $(".snackbar").removeClass("show") }, 3000);


In this script, it checks whether the query passed is undefined or empty. If yes, then the error message which was null earlier is changed and that error is showed up on the screen to the end user. Snackbars animate upwards from the edge of the screen.

        if ($scope.query === '' || $scope.query === undefined) {
            $scope.spinner = false;
            $scope.error = "Please enter a valid Username";



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Filling Audio Buffer to Generate Waves in the PSLab Android App

The PSLab Android App works as an oscilloscope and a wave generator using the audio jack of the Android device. The implementation of the oscilloscope in the Android device using the in-built mic has been discussed in the blog post “Using the Audio Jack to make an Oscilloscope in the PSLab Android App” and the same has been discussed in the context of wave generator in the blog post “Implement Wave Generation Functionality in the PSLab Android App”. This post is a continuation of the post related to the implementation of wave generation functionality in the PSLab Android App. In this post, the subject matter of discussion is the way to fill the audio buffer so that the resulting wave generated is either a Sine Wave, a Square Wave or a Sawtooth Wave. The resultant audio buffer would be played using the AudioTrack API of Android to generate the corresponding wave. The waves we are trying to generate are periodic waves.

Periodic Wave: A wave whose displacement has a periodic variation with respect to time or distance, or both.

Thus, the problem reduces to generating a pulse which will constitute a single time period of the wave. Suppose we want to generate a sine wave; if we generate a continuous stream of pulses as illustrated in the image below, we would get a continuous sine wave. This is the main concept that we shall try to implement using code.

Initialise AudioTrack Object

AudioTrack object is initialised using the following parameters:

  • STREAM TYPE: Type of stream like STREAM_SYSTEM, STREAM_MUSIC, STREAM_RING, etc. For wave generation purposes we are using stream music. Every stream has its own maximum and minimum volume level.  
  • SAMPLING RATE: It is the rate at which the source samples the audio signal.
  • BUFFER SIZE IN BYTES: Total size of the internal buffer in bytes from where the audio data is read for playback.
  • MODES: There are two modes-
    • MODE_STATIC: Audio data is transferred from Java to the native layer only once before the audio starts playing.
    • MODE_STREAM: Audio data is streamed from Java to the native layer as audio is being played.

getMinBufferSize() returns the estimated minimum buffer size required for an AudioTrack object to be created in the MODE_STREAM mode.

minTrackBufferSize = AudioTrack.getMinBufferSize(SAMPLING_RATE, AudioFormat.CHANNEL_OUT_MONO, AudioFormat.ENCODING_PCM_16BIT);
audioTrack = new AudioTrack(

Fill Audio Buffer to Generate Sine Wave

Depending on the values in the audio buffer, the wave is generated by the AudioTrack object. Therefore, to generate a specific kind of wave, we need to fill the audio buffer with some specific values. The values are governed by the wave equation of the signal that we want to generate.

public short[] createBuffer(int frequency) {
   short[] buffer = new short[minTrackBufferSize];
   double f = frequency;
   double q = 0;
   double level = 16384;
   final double K = 2.0 * Math.PI / SAMPLING_RATE;

   for (int i = 0; i < minTrackBufferSize; i++) {
         f += (frequency - f) / 4096.0;
         q += (q < Math.PI) ? f * K : (f * K) - (2.0 * Math.PI);
         buffer[i] = (short) Math.round(Math.sin(q));
   return buffer;

Fill Audio Buffer to Generate Square Wave

To generate a square wave, let’s assume the time period to be t units. So, we need the amplitude to be equal to A for t/2 units and -A for the next t/2 units. Repeating this pulse continuously, we will get a square wave.

buffer[i] = (short) ((q > 0.0) ? 1 : -1);

Fill Audio Buffer to Generate Sawtooth Wave

Ramp signals increases linearly with time. A Ramp pulse has been illustrated in the image below:

We need repeated ramp pulses to generate a continuous sawtooth wave.

buffer[i] = (short) Math.round((q / Math.PI));

Finally, when the audio buffer is generated, write it to the audio sink for playback using write() method exposed by the AudioTrack object.

audioTrack.write(buffer, 0, buffer.length);


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Implementing Order Statistics API on Tickets Route in Open Event Frontend

The order statistics API endpoints are used to display the statistics related to tickets, orders, and sales. It contains the details about the total number of orders, the total number of tickets sold and the amount of the sales. It also gives the detailed information about the pending, expired, placed and completed orders, tickets, and sales.

This article will illustrate how the order statistics can be displayed using the Order Statistics API in Open Event Frontend. The primary end point of Open Event API with which we are concerned with for statistics is

GET /v1/events/{event_identifier}/order-statistics

First, we need to create a model for the order statistics, which will have the fields corresponding to the API, so we proceed with the ember CLI command:

ember g model order-statistics-tickets

Next, we need to define the model according to the requirements. The model needs to extend the base model class. The code for the model looks like this:

import attr from 'ember-data/attr';
import ModelBase from 'open-event-frontend/models/base';

export default ModelBase.extend({
  orders  : attr(),
  tickets : attr(),
  sales   : attr()

As we need to display the statistics related to orders, tickets, and sales so we have their respective variables inside the model which will fetch and store the details from the API.

Now, after creating a model, we need to make an API call to get the details. This can be done using the following:

return this.modelFor('events.view').query('orderStatistics', {});

Since the tickets route is nested inside the event.view route so, first we are getting the model for event.view route and then we’re querying order statistics from the model.

The complete code can be seen here.

Now, we need to call the model inside the template file to display the details. To fetch the total orders we can write like this



In a similar way, the total sales can be displayed like this.



And total tickets can be displayed like this



If we want to fetch other details like the pending sales or completed orders then the only thing we need to replace is the total attribute. In place of total, we can add any other attribute depending on the requirement. The complete code of the template can be seen here.

The UI for the order statistics on the tickets route looks like this.

Fig. 1: The user interface for displaying the statistics

The complete source code can be seen here.


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Implementing Pages API in Open Event Frontend

The pages endpoints are used to create static pages which such as about page or any other page that doesn’t need to be updated frequently and only a specific content is to be shown. This article will illustrate how the pages can be added or removed from the /admin/content/pages route using the pages API in Open Event Frontend. The primary end point of Open Event API with which we are concerned with for pages is

GET /v1/pages

First, we need to create a model for the pages, which will have the fields corresponding to the API, so we proceed with the ember CLI command:

ember g model page

Next, we need to define the model according to the requirements. The model needs to extend the base model class. The code for the page model looks like this:

import attr from 'ember-data/attr';
import ModelBase from 'open-event-frontend/models/base';

export default ModelBase.extend({
  name        : attr('string'),
  title       : attr('string'),
  url         : attr('string'),
  description : attr('string'),
  language    : attr('string'),
  index       : attr('number', { defaultValue: 0 }),
  place       : attr('string')

As the page will have name, title, url which will tell the URL of the page, the language, the description, index and the place of the page where it has to be which can be either a footer or an event.

The complete code for the model can be seen here.

Now, after creating a model, we need to make an API call to get and post the pages created. This can be done using the following:

return this.get('store').findAll('page');

The above line will check the store and find all the pages which have been cached in and if there is no record found then it will make an API call and cache the records in the store so that when called it can return it immediately.

Since in the case of pages we have multiple options like creating a new page, updating a new page, deleting an existing page etc. For creating and updating the page we have a form which has the fields required by the API to create the page.  The UI of the form looks like this.

Fig. 1: The user interface of the form used to create the page.

Fig. 2: The user interface of the form used to update and delete the already existing page

The code for the above form can be seen here.

Now, if we click the items which are present in the sidebar on the left, it enables us to edit and update the page by displaying the information stored in the form and then the details be later updated on the server by clicking the Update button. If we want to delete the form we can do so using the delete button which first shows a pop up to confirm whether we actually want to delete it or not. The code for displaying the delete confirmation pop up looks like this.

<button class="ui red button" 
{{action (confirm (t 'Are you sure you would like to delete this page?') (action 'deletePage' data))}}>
{{t 'Delete'}}</button>


The code to delete the page looks like this

deletePage(data) {
    if (!this.get('isCreate')) {
      this.set('isFormOpen', false);

In the above piece of code, we’re checking whether the form is in create mode or update mode and if it’s in create mode then we can destroy the record and then close the form.

The UI for the pop up looks like this.

Fig.3: The user interface for delete confirmation pop up

The code for the entire process of page creation to deletion can be checked here

To conclude, this is how we efficiently do the process of page creation, updating and deletion using the Open-Event-Orga pages API  ensuring that there is no unnecessary API call to fetch the data and no code duplication.


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Making Skill Display Cards Identical in SUSI.AI Skill CMS

SUSI.AI Skill CMS shows all the skills of SUSI.AI. The cards used to display all the skills follow flexbox structure and adjust their height according to content. This lead to cards of different sizes and this needed to be fixed. This needed to fix as the cards looked like this:

The cards display following things:

  • Image related to skill
  • An example query related to skill in double quotes
  • Name of skill
  • Short description of skill

Now to get all these, we make an ajax call to the following endpoint:'+ this.state.modelValue + '&group=' + this.state.groupValue + '&language=' + this.state.languageValue


  • this.state.modelValue: This is the model of the skill, stored in state of component
  • this.state.groupValue: This represents the group to which skill belongs to. For example Knowledge, Communication, Music, and Audio, etc.
  • this.state.languageValue: This represents the ISO language code of language in which skill is defined

Now the response is in JSONP format and it looks like:

Now we parse the response to get the information needed and return the following Card(Material UI Component):

<Link key={el}
        pathname: '/' + self.state.groupValue + '/' + el + '/' + self.state.languageValue,
            state: {
                        url: url,
                        element: el,
                        name: el,
                        modelValue: self.state.modelValue,
                        groupValue: self.state.groupValue,
                        languageValue: self.state.languageValue,
           <Card style={styles.row} key={el}>
                <div style={styles.right} key={el}>
                       {image ? <div style={styles.imageContainer}>
                        <img alt={skill_name}
                          style={styles.image} />
                          </div> :
                         <CircleImage name={el} size='48' />}
                             <div style={styles.titleStyle}>{examples}</div>
                             <div style={styles.details}>
                                 <h3 style={}>{skill_name}</h3>
                                 <p style={styles.description}>{description}</p>

Now the information that leads to non-uniformity in these cards is the skill description. Now to solve this we decided to put a certain limit to the description length and if that limit is crossed, then we will show the following dots: “”. The height and width of the cards were fixed according to screen size and we modified the description as follows:

if (skill.descriptions) {
      if (skill.descriptions.length > 120) {
          description = skill.descriptions.substring(0, 119) + '...';
      else {
          description = skill.descriptions;

This way no content was being cut and all the skill cards looks identical:


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Implementing Author’s Skill Page in SUSI.AI CMS

SUSI.AI Skill CMS is improving every day and we keep adding new features to it. Recently a feature was added to display all the skills by an author. This feature only showed the list of skills. The user might want to visit the skill page to see the description so we linked the skills on the list to skill page. The list looked like this:

We need to link skill name and image to respective skill page. Now since this is react based app, we do not have different URL for different skills due to SPA. The description, images and other relevant details of skills were being passed as props. We needed to have routes through which we can directly access the skill. This was done by implementing child routes for Skill CMS. Earlier the description, images, and other relevant data was being passed as props from the BrowseSkill component, but now we need to derive this from the URL:

let baseUrl = '';           
let modelValue = "general"; = this.props.location.pathname.split('/')[2];
this.groupValue = this.props.location.pathname.split('/')[1];
this.languageValue = this.props.location.pathname.split('/')[3];
url = baseUrl + '?model=' + modelValue + '&group=' + this.groupValue +        '&language=' + this.languageValue + '&skill=' +;

We now make an ajax call to this URL for fetching the data:

               url: url,
               jsonpCallback: 'pc',
               dataType: 'jsonp',
               jsonp: 'callback',
               crossDomain: true,
               success: function (data) {

This updates the skill page with the description, image, author and other relevant details of the skills. Now all left to do is link the skills on the list to their respective links. This is done by following code:

We define skillURL as:

let skillURL = '' + parse[6] + '/' + parse[8].split('.')[0] + '/' + parse[7];

Here parse is an array which contains model, group and ISO language code of the skill. We updated the Image and text component as:

   href={skillURL} >
     unloader={<CircleImage name={name} size="40"/>}
   className="effect-underline" >

Now after proper styling, we had the following looking skill list by author:


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