Implementing Speech to Text for Chrome in SUSI Web Chat

SUSI Web Chat now replies to voice inputs. To achieve this, I made use of the Web Speech API. The voice input saves one from the pain of typing and it’s a much needed feature for the Web Chat and to maintain the similarity with the other SUSI Android and SUSI iOS clients.

To test the feature out in SUSI Web Chat, click on the microphone icon beside the text area on chat.susi.ai.

Say the message once the dialog appears, and you will see the message being sent to the Chat List rendered in text.

Let’s achieve the same result following the steps below.

  1. First, initialize the class Voice Recognition with defaults for the Speech Recognition, for that we create a file VoiceRecognition.js
  1. We first initialize the Speech Recognition API with the window object.
  2. We warn the User with a console message if there is no Speech Recognition API available.
  3. If it’s available call the recognition function using the following line

this.recognition = this.createRecognition(SpeechRecognition)

// Initialise the Speech recognition API
const SpeechRecognition = window.SpeechRecognition
      || window.webkitSpeechRecognition
      || window.mozSpeechRecognition
      || window.msSpeechRecognition
      || window.oSpeechRecognition
    // Warn the user if not available otherwise call the createRecognition function
    if (SpeechRecognition != null) {
      this.recognition = this.createRecognition(SpeechRecognition)
    } else {
      console.warn('The current browser does not support the SpeechRecognition API.');
    }
  }
  1. Then we write the createRecognition function
  1. We set our defaults first as “continuous  – true, interimResults – false, and language – ‘en-US’ ”
  2. We pass these options to the recognition object that we created in the above step and finally return the recognition object.
createRecognition = (SpeechRecognition) => {
    const defaults = {
      continuous: true,
      interimResults: false,
      lang: 'en-US'
    }

    const options = Object.assign({}, defaults, this.props)

    let recognition = new SpeechRecognition()

    recognition.continuous = options.continuous
    recognition.interimResults = options.interimResults
    recognition.lang = options.lang

    return recognition
  }
  1. Initialize all the helper functions to be passed as props.
  1. start – This method starts the recognition and invokes the Mic of the browser. It also checks if the browser has the access to the user’s Mic.
  2. stop – Stop method closes the Mic and returns the audio captured so far.
  3. abort – Abort method stops the SpeechRecognition service.
  4. onspeechend – This method is called if there is any inactivity and there is no voice input. Hence, stops the recognition service.
  5. componentWillReceiveProps – This method waits for the stop method and calls it when it has received the stop object.
  6. componentWIllUnmount – This method is invoked just before the component is about to unmount and therefore its function is to abort the Speech Recognition Service
  7. render –  We return null as there is nothing to return in this component and all the converted text of the captured Speech will be sent to the parent element.
start = () => {
    this.recognition.start()
  }

  stop = () => {
    this.recognition.stop()
  }

  abort = () => {
    this.recognition.abort()
  }
  onspeechend = () => {
    console.log('no sound detected');
    this.recognition.stop()
  }

  componentWillReceiveProps ({ stop }) {
    if (stop) {
      this.stop()
    }
  }

  componentWillUnmount () {
    this.abort()
  }

  render () {
    return null
  }
  1. Add event listeners to start and stop functions inside componentDidMount() to ensure every action that we want to perform from the parent element is after the component has successfully mounted itself.
  1. start – The start method is set with an action start so that we can pass the required action name to the VoiceRecognition component that we created
  2. end – The end method similarly is set with an action end
  3. After setting up the actions we finally call the bindResult function with the result that we received.
componentDidMount () {
    const events = [
      { name: 'start', action: this.props.onStart },
      { name: 'end', action: this.props.onEnd },
      { name: 'onspeechend', action: this.props.onspeechend }
    ]

    events.forEach(event => {
      this.recognition.addEventListener(event.name, event.action)
    })

    this.recognition.addEventListener('result', this.bindResult)

    this.start()
  }
  1. Bind the result and send it as the props to the parent element.
  2. Combine all interim results of the recognition and send it to the onResult function as finalTranscript
  3. The function bindResult – The function bindResult does all the binding of the interim results that we received and output a final result as finalTranscript.
  4. Lastly, we add the prop validations to ensure the correct props are being passed to our VoiceRecognition component.
// bindResult function
 bindResult = (event) => {
    let interimTranscript = ''
    let finalTranscript = ''
   // Bind all the results to finalTranscript
    for (let i = event.resultIndex; i < event.results.length; ++i) {
      if (event.results[i].isFinal) {
        finalTranscript += event.results[i][0].transcript
      } else {
        interimTranscript += event.results[i][0].transcript
      }
    }

    this.props.onResult({ interimTranscript, finalTranscript })
  }
// Add Prop Validations
VoiceRecognition.propTypes = {
  onStart: PropTypes.func,
  onEnd : PropTypes.func,
  onResult: PropTypes.func,
  Onspeechend: PropTypes.func,
  continuous: PropTypes.bool,
  lang: PropTypes.string,
  stop: PropTypes.bool
};
// Finally export the VoiceRecognition Component
export default VoiceRecognition
  1. Lastly, call the VoiceRecogntion component and pass the props from the MessageComposer Section to it in the following way.
  1. Initialize the default state in the constructor inside this.state
this.state = {
      text: '',
      start: false, // Starting the VoiceRecognition
      stop: false, // Stop the VoiceRecognition
      open: false, // Maintain the modal state
      result:'' // Maintain the result state
    };
  1. onStart function to call the VoiceRecognition component only when the Mic Button is pressed.
  2. onEnd to end the Speech Recognition service.
  3. onResult to send the message through the Actions.createMessage() function
onResult = ({interimTranscript,finalTranscript }) => {
    let result = interimTranscript;
    let voiceResponse = false;
    this.setState({result:result});
    if(finalTranscript) {
      result = finalTranscript;
      this.setState({
      start: false,
      result:result,
      stop: false,
      open:false,
      animate:false
      });
      if(this.props.speechOutputAlways || this.props.speechOutput){
        voiceResponse = true;
      }
      Actions.createMessage(result, this.props.threadID, voiceResponse);
      setTimeout(()=>this.setState({result: ''}),400);
      this.Button = <Mic />
    }
  }
  1. Fire the component based on the value of start variable and pass the requisite props as given below in the code.
// Only when the start is ‘true’ call the VoiceRecognition component

    {this.state.start && (
          <VoiceRecognition
            onStart={this.onStart}
            onEnd={this.onEnd}
            onResult={this.onResult}
            continuous={true}
            lang="en-US"
            stop={this.state.stop}
          />
        )}

 

  1. Update the text in the “Speak Now” Dialog to show the user the Speech to Text conversion
  1. Update the text in the Modal when it is converted from Speech to Text, i.e. when we set the state of the result variable.
{this.state.result !=='' ? this.state.result :
          'Speak Now...'}

To get access to the full code, go to the repository https://github.com/fossasia/chat.susi.ai

Resources

Continue ReadingImplementing Speech to Text for Chrome in SUSI Web Chat

Implementing Text to Speech on SUSI Web Chat

SUSI Web Chat now gives voice replies while chatting with it similar to SUSI Android and SUSI iOS clients. To test the Voice Output on Chrome,

  1. Visit chat.susi.ai
  2. Click on the Mic input button.
  3. Say something using the Mic when the Speak Now View appears

The simplest way to add text-to-speech to your website is by using the official Speech API currently available for Chrome Browser. The following steps help to achieve it in ReactJS.

  1. Initialize state defaults in a component named, VoicePlayer.
const defaults = {
      text: '',
      volume: 1,
      rate: 1,
      pitch: 1,
      lang: 'en-US'
    } 

There are two states which need to be maintained throughout the component and to be passed as such in our props which will maintain the state. Thus our state is simply

this.state = {
      started: false,
      playing: false
    }
  1. Our next step is to make use of functions of the Web Speech API to carry out the relevant processes.
  1. speak() – window.speechSynthesis.speak(this.speech) – Calls the speak method of the Speech API
  2. cancel() – window.speechSynthesis.cancel() – Calls the cancel method of the Speech API
  1. We then use our component helper functions to assign eventListeners and listen to any changes occurring in the background. For this purpose we make use of the functions componentWillReceiveProps(), shouldComponentUpdate(), componentDidMount(), componentWillUnmount(), and render().
  1. componentWillReceiveProps() – receives the object parameter {pause} to listen to any paused action
  2. shouldComponentUpdate() simply returns false if no updates are to be made in the speech outputs.
  3. componentDidMount() is the master function which listens to the action start, adds the eventListener start and end, and calls the speak() function if the prop play is true.
  4. componentWillUnmount() destroys the speech object and ends the speech.

Here’s a code snippet for Function componentDidMount()

componentDidMount () {
  
    const events = [
      { name: 'start', action: this.props.onStart }
    ]
    // Adding event listeners
    events.forEach(e => {
      this.speech.addEventListener(e.name, e.action)
    })

    this.speech.addEventListener('end', () => {
      this.setState({ started: false })
      this.props.onEnd()
    })

    if (this.props.play) {
      this.speak()
    }
  }
  1. We then add proper props validation in the following way to our VoicePlayer component.
VoicePlayer.propTypes = {
  play: PropTypes.bool,
  text: PropTypes.string,
  onStart: PropTypes.func,
  onEnd: PropTypes.func
};
  1. The next step is to pass the props from a listener view to the VoicePlayer component. Hence the listener here is the component MessageListItem.js from where the voice player is initialized.
  1. First step is to initialise the state.
this.state = {
      play: false,
    }
  onStart = () => {
    this.setState({ play: true });
  }
  onEnd = () => {
    this.setState({ play: false });
  }
  1. Next, we set play to true when we want to pass the props and the text which is to be said and append it to the message lists which have voice set as `true`
 { this.props.message.voice &&
      (<VoicePlayer
             play
             text={voiceOutput}
             onStart={this.onStart}
             onEnd={this.onEnd}
 />)}

Finally, our message lists with voice true will be heard on the speaker as they have been spoken on the microphone. To get access to the full code, go to the repository https://github.com/fossasia/chat.susi.ai or on our chat channel at gitter.im/fossasia/susi_webchat

Resources

  1. Speak-easy-synthesis repository http://mdn.github.io/web-speech-api/speak-easy-synthesis
  2. Web-speech-api repository https://github.com/mdn/web-speech-api/
Continue ReadingImplementing Text to Speech on SUSI Web Chat

Exporting Functions in PSLab Firmware

Computer programs consist of several hundreds line of code. Smaller programs contain around few hundreds while larger programs like PSLab firmware contains lines of code expanding over 2000 lines. The major drawback with a code with lots of lines is the difficulty to debug and hardship for a new developer to understand the code. As a solution modularization techniques can be used to have the long code broken down to small set of codes. In C programming this can be achieved using different .c files and relevant .h(header) files.

The task is tricky as the main code contains a lot of interrelated functions and variables. Lots of errors were encountered when the large code in pslab-firmware being modularized into application specific files. In a scenario like this, global variables or static variables were a much of a help.

Global Variables in C

A global variable in C is a variable whose scope spans wide across the entire program. Updation to the variable will be reflected everywhere it is used.

extern TYPE VARIABLE = VALUE;

Static Variables in C

This type of variables preserve their content regardless of the scope they are in.

static TYPE VARIABLE = VALUE;

Both the variables preserve their values but the memory usage is different depending on the implementation. This can be explained using a simple example.

Suppose a variable is required in different C files and it is defined in one of the header files as a local variable. The header file is then added to several other c files. When the program is compiled the compiler will create several copies of the same variable which will throw a compilation error as variable is already declared. In PSLab firmware, a variable or a method from one library has a higher probability of it being used in another one or many libraries.

This issue can be addressed in two different ways. They are by using static variables or global variables. Depending on the selection, the implementation is different.

The first implementation is using static variables. This type of variables at the time of compilation, create different copies of himself in different c files. Due to the fact that C language treats every C file as a separate program, if we include a header file with static variables in two c files, it will create two copies of the same variable. This will avoid the error messages with variables redeclared. Even though this fixes the issue in firmware, the memory allocation will be of a wastage. This is the first implementation used in PSLab firmware. The memory usage was very high due to duplicate variables taking much memory than they should take. This lead to the second implementation.

first_header.h

#ifndef FIRST_HEADER_H 
#define FIRST_HEADER_H 

static int var_1;

#endif 

/* FIRST_HEADER_H */

second_header.h

#ifndef SECOND_HEADER_H
#define SECOND_HEADER_H

static int var_1;

#endif    

/* SECOND_HEADER_H */

first_header.c

#include <stdio.h>
#include "first_header.h"
#include "second_header.h"

int main() {
    var_1 = 10;
    printf("%d", var_1);
}

The next implementation uses global variables. This type of variables need to be declared only in one header file and can be reused by declaring the header file in other c files. The global variables must be declared in a header file with the keyword extern and defined in the relevant c file once. Then it will be available throughout the application and no errors of variable redeclaration will occur while compiling. This became the final implementation for the PSLab-firmware to fix the compilation issues modularizing application specific C and header files.

Resources:

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Persistence Layer in Open Event Organizer Android App

Open Event Organizer is an Event Managing Android App with the core features of Attendee Check In by QR Code Scan and Data Sync with the Open Event API Server. As an event can be large, so the app will be dealing with a large amount of a data. Hence to avoid repetitive network requests for fetching the data, the app maintains a local database containing all the required data and the database is synced with the server. Android provides android.database.sqlite package which contains the API needed to use the database on the Android. But it is really not a good practice to use the sqlite queries everywhere in the app. So there comes a persistence layer. A persistence layer works between the database and the business logic. Open Event Organizer uses Raizlabs’s DbFlow, an ORM based Android Database Library for the same. I will be talking about its implementation through the app in this blog.

First of all, you declare the base class of the database which is used to create the database by Android for the app. You declare all the base constants here. The class looks like:

@Database(
   name = OrgaDatabase.NAME,
   version = OrgaDatabase.VERSION,
   ...
)
public class OrgaDatabase {
   public static final String NAME = "orga_database";
   public static final int VERSION = 2;
   ...
}

OrgaDatabase.java
app/src/main/java/org/fossasia/openevent/app/data/db/configuration/OrgaDatabase.java

Initialise the database in the Application class using FlowManager provided by the library. Choose the Application class to do this to ensure that the library finds the generated code in the DbFlow.

FlowManager.init(
   new FlowConfig.Builder(context)
       .addDatabaseConfig(
           new DatabaseConfig.Builder(OrgaDatabase.class)
           ...
           .build()
       )
       .build());

OrgaApplication.java
app/src/main/java/org/fossasia/openevent/app/OrgaApplication.java

The database is created now. For tables creation, DbFlow uses model classes which must be annotated using the annotations provided by the library. The basic annotations are – @Table, @PrimaryKey, @Column, @ForeignKey etc.

For example, the Attendee class in the app looks like:

@Table(database = OrgaDatabase.class)
public class Attendee ... {

   @PrimaryKey
   public long id;

   @Column
   public boolean checkedIn;
   ...
   ...
   @ForeignKey(
       onDelete = ForeignKeyAction.CASCADE,
       onUpdate = ForeignKeyAction.CASCADE)
   public Order order;
   ...
}

Attendee.java
app/src/main/java/org/fossasia/openevent/app/data/models/Attendee.java

This will create a table named attendee with the columns and relationships annotated. Now comes the part of accessing data from the database. Open Event App uses RxJava’s support to the DbFlow library which enables async data accessing. The getItems method from DataBaseRepository looks like:

public <T> Observable<T> getItems(Class<T> typeClass, SQLOperator... conditions) {
   return RXSQLite.rx(SQLite.select()
       .from(typeClass)
       .where(conditions))
       .queryList()
       .flattenAsObservable(items -> items);
}

 

The method returns an observable emitting the items from the result. For data saving, the method looks like:

DatabaseDefinition database = FlowManager.getDatabase(OrgaDatabase.class);
FastStoreModelTransaction<T> transaction = FastStoreModelTransaction
   .insertBuilder(FlowManager.getModelAdapter(itemClass))
   .addAll(items)
   .build();
database.executeTransaction(transaction);

 

And for updating data, the method looks like:

ModelAdapter<T> modelAdapter = FlowManager.getModelAdapter(classType);
modelAdapter.update(item);

DatabaseRepository.java
app/src/main/java/org/fossasia/openevent/app/data/db/DatabaseRepository.java

DbFlow provides DirectModelNotifier which is used to get notified of the database change anywhere in the app. Open Event App uses PublishSubjects to send notifications on database change event. The implementation of the DatabaseChangeListener in the app looks like:

public class DatabaseChangeListener<T> ... {
   private PublishSubject<ModelChange<T>> publishSubject = PublishSubject.create();
   private DirectModelNotifier.ModelChangedListener<T> modelModelChangedListener;
   ...
   public void startListening() {
       modelModelChangedListener = new DirectModelNotifier.ModelChangedListener<T>() {
           @Override
           public void onTableChanged(@Nullable Class<?> aClass, @NonNull BaseModel.Action action) {
               // No action to be taken
           }
           @Override
           public void onModelChanged(@NonNull T model, @NonNull BaseModel.Action action) {
               publishSubject.onNext(new ModelChange<>(model, action));
           }
       };
       DirectModelNotifier.get().registerForModelChanges(classType, modelModelChangedListener);
   }
   ...
}

DatabaseChangeListener.java
app/src/main/java/org/fossasia/openevent/app/data/db/DatabaseChangeListener.java

The class is used in the app to get notified of the data change and to update the required local data fields using data from item emitted by the publishSubject of the class. This is used in the app where same data is accessed at more than one places. For example, There are two fragments – AttendeesFragment and AttendeeCheckInFragment from which an attendee’s check in status is toggled. So when the status is toggled from AttendeeCheckInFragment, the change must be updated in the AttendeesFragment’s attendees list. This is carried out using DatabaseChangeListener in the AttendeesPresenter which provides attendees list to the AttendeesFragment. And on the change in the attendee’s check in status, AttendeePresenter’s attendeeListener listens for the change and update the attendee in the list accordingly.

Links:
1. Raizlabs’s DbFlow , an ORM Android Database Library Github Repo Link
2. DbFlow documentation
3. Android database managing API android.database.sqlite

Continue ReadingPersistence Layer in Open Event Organizer Android App

Image Uploading in Open Event API Server

Open Event API Server manages image uploading in a very simple way. There are many APIs such as “Event API” in API Server provides you data pointer in request body to send the image URL. Since you can send only URLs here if you want to upload any image you can use our Image Uploading API. Now, this uploading API provides you a temporary URL of your uploaded file. This is not the permanent storage but the good thing is that developers do not have to do anything else. Just send this temporary URL to the different APIs like the event one and rest of the work is done by APIs.
API Endpoints which receives the image URLs have their simple mechanism.

  • Create a copy of an uploaded image
  • Create different sizes of the uploaded image
  • Save all images to preferred storage. The Super Admin can set this storage in admin preferences

To better understand this, consider this sample request object to create an event

{
  "data": {
    "attributes": {
      "name": "New Event",
      "starts-at": "2002-05-30T09:30:10+05:30",
      "ends-at": "2022-05-30T09:30:10+05:30",
      "email": "example@example.com",
      "timezone": "Asia/Kolkata",
      "original-image-url": "https://cdn.pixabay.com/photo/2013/11/23/16/25/birds-216412_1280.jpg"
    },
    "type": "event"
  }
}

I have provided one attribute as “original-image-url”, server will open the image and create different images of different sizes as

      "is-map-shown": false,
      "original-image-url": "http://example.com/media/events/3/original/eUpxSmdCMj/43c6d4d2-db2b-460b-b891-1ceeba792cab.jpg",
      "onsite-details": null,
      "organizer-name": null,
      "can-pay-by-stripe": false,
      "large-image-url": "http://example.com/media/events/3/large/WEV4YUJCeF/f819f1d2-29bf-4acc-9af5-8052b6ab65b3.jpg",
      "timezone": "Asia/Kolkata",
      "can-pay-onsite": false,
      "deleted-at": null,
      "ticket-url": null,
      "can-pay-by-paypal": false,
      "location-name": null,
      "is-sponsors-enabled": false,
      "is-sessions-speakers-enabled": false,
      "privacy": "public",
      "has-organizer-info": false,
      "state": "Draft",
      "latitude": null,
      "starts-at": "2002-05-30T04:00:10+00:00",
      "searchable-location-name": null,
      "is-ticketing-enabled": true,
      "can-pay-by-cheque": false,
      "description": "",
      "pentabarf-url": null,
      "xcal-url": null,
      "logo-url": null,
      "can-pay-by-bank": false,
      "is-tax-enabled": false,
      "ical-url": null,
      "name": "New Event",
      "icon-image-url": "http://example.com/media/events/3/icon/N01BcTRUN2/65f25497-a079-4515-8359-ce5212e9669f.jpg",
      "thumbnail-image-url": "http://example.com/media/events/3/thumbnail/U2ZpSU1IK2/4fa07a9a-ef72-45f8-993b-037b0ad6dd6e.jpg",

We can clearly see that server is generating three other images on permanent storage as well as creating the copy of original-image-url into permanent storage.
Since we already have our Storage class, all we need to do is to make the little bit changes in it due to the decoupling of the Open Event. Also, I had to work on these points below

  • Fix upload module, provide support to generate url of locally uploaded file based on static_domain defined in settings
  • Using PIL create a method to generate new image by converting first it to jpeg(lower size than png) and resize it according to the aspect ratio
  • Create a helper method to create different sizes
  • Store all images in preferred storage.
  • Update APIs to incorporate this feature, drop any URLs in image pointers except original_image_url

Support for generating locally uploaded file’s URL
Here I worked on adding support to check if any static_domain is set by a user and used the request.url as the fallback.

if get_settings()['static_domain']:
        return get_settings()['static_domain'] + \
            file_relative_path.replace('/static', '')
    url = urlparse(request.url)
    return url.scheme + '://' + url.host + file_relative_path

Using PIL create a method to create image

This method is created to create the image based on any size passed it to as a parameter. The important role of this is to convert the image into jpg and then resize it on the basis of size and aspect ratio provided.
Earlier, in Orga Server, we were directly using the “open” method to open Image files but since they are no longer needed to be on the local server, a user can provide the link to any direct image. To add this support, all we needed is to use StringIO to turn the read string into a file-like object

image_file = cStringIO.StringIO(urllib.urlopen(image_file).read())

Next, I have to work on clearing the temporary images from the cloud which was created using temporary APIs. I believe that will be a cakewalk for locally stored images since I already had this support in this method.

if remove_after_upload:
        os.remove(image_file)

Update APIs to incorporate this feature
Below is an example how this works in an API.

if data.get('original_image_url') and data['original_image_url'] != event.original_image_url:
            uploaded_images = create_save_image_sizes(data['original_image_url'], 'event', event.id)
            data['original_image_url'] = uploaded_images['original_image_url']
            data['large_image_url'] = uploaded_images['large_image_url']
            data['thumbnail_image_url'] = uploaded_images['thumbnail_image_url']
            data['icon_image_url'] = uploaded_images['icon_image_url']
        else:
            if data.get('large_image_url'):
                del data['large_image_url']
            if data.get('thumbnail_image_url'):
                del data['thumbnail_image_url']
            if data.get('icon_image_url'):
                del data['icon_image_url']

Here the method “create_save_image_sizes” provides the different URL of different images of different sizes and we clearly dropping any other images of different sizes is provided by the user.

General Suggestion
Sometimes when we work on such issues there are some of the things to take care of for example, if you checked the first snippet, I tried to ensure that you will get the URL although it is sure that static_domain will not be blank, because even if the user (admin) doesn’t fill that field then it will be filled by server hostname
A similar situation is the one where there is no record in Image Sizes table, may be server admin didn’t add one. In that case, it will use the standard sizes stored in the codebase to create different images of different sizes.

Resources:

Continue ReadingImage Uploading in Open Event API Server

Adding Unit Tests for Services in loklak search

In Loklak search, it can be tricky to write tests for services as these services are customizable and not fixed. Therefore, we need to test every query parameter of the URL. Moreover, we need to test if service is parsing data in a correct manner and returns only data of type ApiResponse.

In this blog here, we are going to see how to build different components for unit testing services. We will be going to test Search service in loklak search which makes Jsonp request to get the response from the loklak search.json API which are displayed as feeds on loklak search. We need to test if the service handles the response in a correct way and if the request parameters are exactly according to customization.

Service to test

Search service in loklak search is one of the most important component in the loklak search. SearchService is a class with a method fetchQuery() which takes parameter and sets up URL parameters for the search.json API of loklak. Now, it makes a JSONP request and maps the API response. The Method fetchQuery() can be called from other components with parameters query and lastRecord to get the response from the server based on a certain search query and the last record to implement pagination feature in loklak search. Now as the data is retrieved, a callback function is called to access the response returned by the API. Now, the response received from the server is parsed to JSON format data to extract data from the response easily.

@Injectable()
export class SearchService {
private static readonly apiUrl: URL = new URL(‘http://api.loklak.org/api/search.json’);
private static maximum_records_fetch = 20;
private static minified_results = true;
private static source = ‘all’;
private static fields = ‘created_at,screen_name,mentions,hashtags’;
private static limit = 10;
private static timezoneOffset: string = new Date().getTimezoneOffset().toString();constructor(
private jsonp: Jsonp
) { }// TODO: make the searchParams as configureable model rather than this approach.
public fetchQuery(query: string, lastRecord = 0): Observable<ApiResponse> {
const searchParams = new URLSearchParams();
searchParams.set(‘q’, query);
searchParams.set(‘callback’, ‘JSONP_CALLBACK’);
searchParams.set(‘minified’, SearchService.minified_results.toString());
searchParams.set(‘source’, SearchService.source);
searchParams.set(‘maximumRecords’, SearchService.maximum_records_fetch.toString());
searchParams.set(‘timezoneOffset’, SearchService.timezoneOffset);
searchParams.set(‘startRecord’, (lastRecord + 1).toString());
searchParams.set(‘fields’, SearchService.fields);
searchParams.set(‘limit’, SearchService.limit.toString());
return this.jsonp.get(SearchService.apiUrl.toString(), { search: searchParams })
.map(this.extractData)}private extractData(res: Response): ApiResponse {
try {
return <ApiResponse>res.json();
} catch (error) {
console.error(error);
}
}

Testing the service

  • Create a mock backend to assure that we are not making any Jsonp request. We need to use Mock Jsonp provider for this. This provider sets up MockBackend and wires up all the dependencies to override the Request Options used by the JSONP request.

const mockJsonpProvider = {
provide: Jsonp,
deps: [MockBackend, BaseRequestOptions],
useFactory: (backend: MockBackend, defaultOptions: BaseRequestOptions) => {
return new Jsonp(backend, defaultOptions);
}
};

 

  • Now, we need to configure the testing module to isolate service from other dependencies. With this, we can instantiate services manually. We have to use TestBed for unit testing and provide all necessary imports/providers for creating and testing services in the unit test.

describe(‘Service: Search’, () => {
let service: SearchService = null;
let backend: MockBackend = null;
beforeEach(() => {
TestBed.configureTestingModule({
providers: [
MockBackend,
BaseRequestOptions,
mockJsonpProvider,
SearchService
]
});
});

 

  • Now, we will inject Service (to be tested) and MockBackend into the Testing module. As all the dependencies are injected, we can now initiate the connections and start testing the service.

beforeEach(inject([SearchService, MockBackend], (searchService: SearchService, mockBackend: MockBackend) => {
service = searchService;
backend = mockBackend;
}));

 

  • We will be using it() block to mention about what property/feature we are going to test in the block. All the tests will be included in this block. One of the most important part is to induce callback function done which will close the connection as soon the testing is over.

it(‘should call the search api and return the search results’, (done)=>{
// test goes here
});

 

  • Now, we will create a connection to the MockBackend and subscribe to this connection. We need to configure ResponseOptions so that mock response is JSONified and returned when the request is made.  Now, the MockBackend is set up and we can proceed to make assertions and test the service.

const result = MockResponse;
backend.connections.subscribe((connection: MockConnection) => {
const options = new ResponseOptions({
body: JSON.stringify(result)
});
connection.mockRespond(new Response(options));

 

  • We can now add test by using expect() block to check if the assertion is true or false. We will now test:
    • Request method: We will be testing if the request method used by the connection created is GET.

expect(connection.request.method).toEqual(RequestMethod.Get);
    • Request Url: We will be testing if all the URL Search Parameters are correct and according to what we provide as a parameter to the method fetchQuery().

expect(connection.request.url).toEqual(
`http://api.loklak.org/api/search.json` +
`?q=${query}` +
`&callback=JSONP_CALLBACK` +
`&minified=true&source=all` +
`&maximumRecords=20&timezoneOffset=${timezoneOffset}` +
`&startRecord=${lastRecord + 1}` +
`&fields=created_at,screen_name,mentions,hashtags&limit=10`);
});
);

 

  • Response:  Now, we need to call the service to make a request to the backend and subscribe to the response returned. Next, we will make an assertion to check if the response returned and parsed by the service is equal the Mock Response that should be returned. At the end, we need to call the callback function done() to close the connection.

service
.fetchQuery(query, lastRecord)
.subscribe((res) => {
expect(res).toEqual(result);
done();
});
});

Reference

Continue ReadingAdding Unit Tests for Services in loklak search

Permission Manager in Open Event API Server

Open Event API Server uses different decorators to control permissions for different access levels as discussed here. Next challenging thing for permissions was reducing redundancy and ensuring permission decorators are independent of different API views. They should not look to the view for which they are checking the permission or some different logic for different views.

In API Server, we have different endpoints that leads to same Resource this way we maintain relationships between different entities but this leads to a problem where permission decorators has to work on different API endpoints that points to different or same resource and but to check a permission some attributes are required and one or more endpoints may not provide all attributes required to check a permission.

For instance, PATCH /session/id` request requires permissions of a Co-Organizer and permission decorator for this requires two things, user detail and event details. It is easy to fetch user_id from logged in user while it was challenging to get “event_id”. Therefore to solve this purpose I worked on a module named “permission_manager.py” situated at “app/api/helpers/permission_manager.py” in the codebase

Basic Idea of Permission Manager

Permission manager basically works to serve the required attributes/view_kwargs to permission decorators so that these decorators do not break

Its logic can be described as:

    1. It first sits in the middle of a request and permission decorator
    2. Evaluates the arguments passed to it and ensure the current method of the request (POST, GET, etc ) is the part of permission check or not.
    3. Uses two important things, fetch and fetch_as
      fetch => value of this argument is the URL parameter key which will be fetched from URL or the database ( if not present in URL )
      fetch_as => the value received from fetch will be sent to permission decorator by the name as the value of this option.
    4. If the fetch key is not there in URL, It uses third parameter model which is Model if the table from where this key can be fetched and then passes it to permission decorator
    5. Returns the requested view on passing access level and Forbidden error if fails

This way it ensures that if looks for the only specific type of requests allowing us to set different rules for different methods.

if 'methods' in kwargs:
        methods = kwargs['methods']

    if request.method not in methods:
        return view(*view_args, **view_kwargs)

Implementing Permission Manager

Implementing it was a simple thing,

  1. Firstly, registration of JSON API app is shifted from app/api/__init__.py to app/api/bootstrap.py so that this module can be imported anywhere
  2. Added permission manager to the app_v1 module
  3. Created permission_manager.py in app/api/helpers
  4. Added it’s usage in different APIs

An example Usage:

decorators = (api.has_permission('is_coorganizer', fetch='event_id', fetch_as="event_id", methods="POST",
                                     check=lambda a: a.get('event_id') or a.get('event_identifier')),)

Here we are checking if the request has the permission of a Co-Organizer and for this, we need to fetch event_id  from request URI. Since no model is provided here so it is required for event_id in URL this also ensures no other endpoints can leak the resource. Also here we are checking for only POST requests thus it will pass the GET requests as it is no checking.

What’s next in permission manager?

Permission has various scopes for improving, I’m still working on a module as part of permission manager which can be used directly in the middle of views and resources so that we can check for permission for specific requests in the middle of any process.

The ability to add logic so that we can leave the check on the basis of some logic may be adding some lambda attributes will work.

Resources

Continue ReadingPermission Manager in Open Event API Server

Selecting Best persistent storage for Phimpme Android and how to use it

As we are progressing in our Phimpme Android app. I added account manager part which deals with connecting all other accounts to phimpme. Showing a list of connected accounts.

We need a persistent storage to store all the details such as username, full name, profile image url, access token (to access API). I researched on various Object Relation mapping (ORMs) such as:

  1. DBFlow: https://github.com/Raizlabs/DBFlow
  2. GreenDAO: https://github.com/greenrobot/greenDAO
  3. SugarORM: http://satyan.github.io/sugar/
  4. Requery: https://github.com/requery/requery

and other NoSQL databases such as Realm Database : https://github.com/realm/realm-java.

After reading a lot from some blogs on the benchmarking of these ORMs and database, I came to know that Realm database is quite better in terms of Speed of writing data and ease of use.

Steps to integrate Realm Database:

  • Installation of Realm database in android

Following these steps https://realm.io/docs/java/latest/#installation quickly setup realm in android. Add

classpath "io.realm:realm-gradle-plugin:3.3.2"

in Project level build.gradle file and Add

apply plugin: 'realm-android' 

in app level build.gradle, That’s it for using Realm

  • Generating required Realm models

Firstly, make sure what you need to store in your database. In case of phimpme, I first go through the account section and noted down what needs to be there.  Profile image URL, username, full name, account indicator image name. Below image illustrate this better.

This is the Realm Model class I made in Kotlin to store name, username and access token for accessing API.

open class AccountDatabase(
       @PrimaryKey var name: String = "",
       var username: String = "",
       var token: String = ""
) : RealmObject()

  • Writing data in database

In Account manager, I create a add account option from where a dialog appear with a list of accounts. Currently, Twitter is working, when onSuccess function invoke in AccountPickerFragment I start a twitter session and store values in database. Writing data in database:

// Begin realm transaction
realm.beginTransaction();

// Creating Realm object for AccountDatabase Class
account = realm.createObject(AccountDatabase.class,
       accountsList[0]);

account.setUsername(session.getUserName());
account.setToken(String.valueOf(session.getAuthToken()));
realm.commitTransaction();

Begin and commit block in necessary. There is one more way of doing this is using execute function in Realm

  • Use Separate Database Helper class for Database operations

It’s good to use a separate class for all the Database operations needed in the project. I created a DatabaseHelper Class and added a function to query the result needed. Query the database

public RealmResults<AccountDatabase> fetchAccountDetails(){
   return realm.where(AccountDatabase.class).findAll();
}

It give all of the results, stored in the database like below

  • Problems I faced with annotation processor while using Kotlin and Realm together

The Kotlin annotation processor not running due to the plugins wrong order. This issue https://github.com/realm/realm-java/pull/2568 helped me in solving that. I addded apply plugin: ‘kotlin-kapt’. In app gradle file and shift apply plugin: ‘realm-android’ In below the order.

Resources:

 

Continue ReadingSelecting Best persistent storage for Phimpme Android and how to use it

Implementing Wallpapers in React JS SUSI Web Chat Application

The different SUSI AI clients need to match in their feature set. One feature that was missing in the React JS SUSI Web Chat application was the ability for users to change the application wallpaper or background. This is how we implemented it on SUSI Web Chat.
Firstly we added a text field after the circle picker that change the color of the Application body. Because there should be a place to add the wallpaper image URL. Added that text field like this.

   const components = componentsList.map((component) => {
       return

key={component.id} className=‘circleChoose’>

Change color of {component.name}:

 

         color={component} width={'100%'}
         onChangeComplete={ this.handleChangeComplete.bind(this,
         component.component) }
         onChange={this.handleColorChange.bind(this,component.id)}>
       

CirclePicker shows the circular color picker to choose the colors for each component of the application.

        
         name="backgroundImg"
         style={{display:component.component==='body'?'block':'none'}}
         onChange={
           (e,value)=>
           this.handleChangeBackgroundImage(value) }
         value={this.state.bodyBackgroundImage}
          floatingLabelText="Body Background Image URL" />
       

})

In ’TextField’ I have checked below condition whether to display or not to display the text field after the ‘body’ color picker.

style={{display:component.component==='body'?'block':'none'}}

To apply changes as soon as the user enters the image url, we refer the value of the ‘TextField’ and pass it into the ‘handleChangeBackgroundImage()’ function as ‘value’ on change like this.

         onChange={
           (e,value)=>
           this.handleChangeBackgroundImage(value) }

In ‘‘handleChangeBackgroundImage()’ function we change the state of the application and background of the application like this.

  handleChangeBackgroundImage(backImage){
   document.body.style.setProperty('background-image', 'url('+ backImage+')');
   document.body.style.setProperty('background-repeat', 'no-repeat');
   document.body.style.setProperty('background-size', 'cover');
   this.setState({bodyBackgroundImage:backImage});
 }

In here ‘document.body.style.setProperty’ we change the style of the application’s ‘’ tag. This is how wallpapers are changing on SUSI Web Chat Application.

Resources:

React Refs: https://facebook.github.io/react/docs/refs-and-the-dom.html

Refer Value from text field: https://stackoverflow.com/questions/43960183/material-ui-component-reference-does-not-work

Continue ReadingImplementing Wallpapers in React JS SUSI Web Chat Application

Porting Phimpme Android to Kotlin

As we are going ahead in Phimpme Project we are now on verge to start our account manager which deals with sharing images to many platforms right from the app. The account manager will take care of logging In the user. Saving it’s important credentials such access token, username etc as required by the API.

Google IO ‘17 just passed, and we seen tons of new features, APIs and development tools. One of the them is official support for Kotlin in Android Studio.

As stated by the developers at the conference that one best way to work on Kotlin is add today in your project. Because it is compatible with Java, we can work together on both languages in the same project. It is not mandatory for you to shift your entire code to Kotlin to build a project. So starting with the account manager we decided to bring this to our code. It helps in reducing the boilerplate code for example in Phimpme, I created a model for Realm database.

open class AccountDatabase(

       @PrimaryKey var name: String = "",

       var username: String = "",

       var token: String = ""

) : RealmObject()

That’s all I need to create a model class, no need to create getter and setter property

This helps me to get details from getter methods and show on Account Manager Recycler View like below.

Step 1 : Upgrade to Android Studio Preview 3.0

Android Studio Preview 3.0 comes up with all new features and Kotlin support. We all upgraded to that. It has a great Android Profiler with advance features for debugging and logcat is now moved separately. This step is not mandatory, you can work on older version of Android Studio as well.

Step 2 : Configure Kotlin

It’s easy in Android Studio Preview 3.0 to configure Kotlin. Go to Tools → Kotlin → Configure Kotlin in project.

What in the configuration

  • It added a classpath dependency in project level build.gradle file
classpath"org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
  • Added Kotlin plugin
apply plugin: 'kotlin-android'
  • Added kotlin std lib in app level build.gradle
compile "org.jetbrains.kotlin:kotlin-stdlib-jre7:$kotlin_version"

Step 3: How to add Kotlin files

Now your project is ready for Kotlin. In Android Studio Preview 3.0 you can create new Kotlin files from the file menu.

Also by using Activity template you can select the source language as Java or Kotlin as per your preference.

Step 4 : Work with Kotlin

There are a lot new features in Kotlin to explore. Some of them are

  • Null Safety : In Kotlin, the type system distinguishes between references that can hold null (nullable references) and those that can not (non-null references). For example, a regular variable of type String cannot hold null.
var a: String = "abc"
a = null // compilation error

To allow nulls, we can declare a variable as nullable string, written String?:

 var b: String? = "abc"
 b = null // ok
  • Val and Var are two keywords in Kotlin to declare variables. Val gives you read only variable which is same as final modifier in Java, it is not changing. In other words it is immutable Data variables. Var is mutable data variable
  • Semicolons (;) are optional
  • No switch it’s when block in Kotlin. No need to write break and case: below is snippet from phimpme app
override fun onOptionsItemSelected(item: MenuItem): Boolean {
        when (item.itemId) {
            R.id.action_add_account -> {
                val fragmentManager = fragmentManager
                val accountsPicker = AccountPickerFragment().newInstance("Accounts Picker")
                accountsPicker.show(fragmentManager, "Accounts Picker")
            }
            else -> return super.onOptionsItemSelected(item)
        }
        return true
    }


Source:

Continue ReadingPorting Phimpme Android to Kotlin