Storing User Settings on Server in SUSI Web Chat

One of the important features of SUSI Web Chat is that the state of the application is maintained upon logout-login and across all clients. The web chat application provides various settings to a logged in user and each user has his own preferences. So all the settings chosen accordingly by the user must be stored on the server so that whenever a user logs in we pull the users data from the server and initialise the application according to his chosen settings and whenever settings are changed we update them on the server. This helps us maintain the state of the application specific to a given user and also across all clients.

The flow behind the implementation is:

  1. The client fetches the settings upon login and initialises the app accordingly.
  2. Whenever user settings are changed, the client updates the changed settings on the server so that it can be accessed by other clients as well and so, the state is maintained across all chat clients

Let us visit SUSI Web Chat and try it out.

How is this implemented?

We use UserPreferencesStore to store all the settings, and Actions to push and pull user data from the server and update the UserPreferencesStore.

Initialising the User Settings

Whenever the app is initialised, getSettings() function is called first which checks if the user is logged in or not. If the user is not logged in then it returns, else an ajax call is made to the server to get the user settings from the server.

The endpoint used to fetch User Settings is : 

 BASE_URL+'/aaa/listUserSettings.json?access_token=ACCESS_TOKEN'

where BASE_URL is either the standard server i.e http://api.susi.ai/ or the custom server user used while logging in.

The server returns a JSON object with the existing settings stored for that user

{
  "session": {
    "identity": {
      "type": ,
      "name": ,
      "anonymous":
    }
  },
  "settings": {
    "SETTING_NAME": "SETTING_VALUE"
  }
}

These settings are sent to the UserPreferenceStore thorugh the initialiseSettings action.

export function initialiseSettings(settings) {
  ChatAppDispatcher.dispatch({
  type: ActionTypes.INIT_SETTINGS,
  Settings
  });
};

The UserPreferenceStore has a _defaults object which stores all the user settings and is initialised with default values. The store listens to ActionTypes.INIT_SETTINGS event which is triggered by initialiseSettings and the settings are updated in the UserPreferenceStore.

let _defaults = {
  Theme: 'light',    //Theme of the ChatApp
  StandardServer: 'http://api.susi.ai',  //Standard SUSI AI Server Endpoint
  EnterAsSend: true,  //Send Messages on ENTER Key Press
  MicInput: true,  //Enable Speech Input
  SpeechOutput: true,  //Enable Speech Output For Speech Input
  SpeechOutputAlways: false,  //Enable Speech Output regardless of Input    Type
  SpeechRate: 1,  //Rate of Speech Output
  SpeechPitch: 1,  //Pitch of Speech Output
};

Once the settings are updated in UserPreferencesStore, the corresponding changes are emitted which trigger the update of all the components using the values present in UserPreferenceStore.

Pushing the User Settings to Server

Whenever the user changes any settings, apart from updating them locally within the UserPreferenceStore, we also have to push the changes to the server.

When user settings are changed, we first find out only those settings which have been changed and send these changed settings to the UserPreferencesStore to update _defaults through settingsChanged action which calls the dispatcher using SETTINGS_CHANGED action type to pass the data to UserPreferencesStore.

export function settingsChanged(settings) {
  ChatAppDispatcher.dispatch({
  type: ActionTypes.SETTINGS_CHANGED,
  settings
  });
  Actions.pushSettingsToServer(settings);
}

This data is then collected in UserPreferencesStore where the _defaults are updated accordingly.

case ActionTypes.SETTINGS_CHANGED: {
  let settings = action.settings;
  Object.keys(settings).forEach((key) => {
    _defaults[key] = settings[key];
  });
  UserPreferencesStore.emitChange();
  break;
}

We also need to push the user settings to server. We make an ajax call to the server for each setting that has been updated in the pushSettingsToServer action.

The endpoint used to add or update User Settings is : 

BASE_URL+'/aaa/changeUserSettings.json?key=SETTING_NAME&value=SETTING_VALUE&access_token=ACCESS_TOKEN'

where BASE_URL is either the standard server i.e http://api.susi.ai/ or the custom server user used while logging in.

Here, the access_token is also passed in the server call as it is needed by the server to distinguish between logged in and anonymous users. The access_token is stored in cookies when a user logs in and is accessed from cookies whenever required.

This is how user specific data is maintained on the server and is pushed and pulled from the server to maintain the state of the chat app upon login-logout and also across all chat clients without using any local database specific to the clients.

The entire code can be found at SUSI Web Chat Repo.

Resources

Adding API endpoint to SUSI.AI for Skill Historization

SUSI Skill CMS is an editor to write and edit skill easily. It follows an API centric approach where the Susi server acts as API server. Using Skill CMS we can browse history of a skill, where we get commit ID, commit message  and name the author who made the changes to that skills. In this blogpost we will see how to fetch complete commit history of a skill in the susi skill repository. A skill is a set of intents. One text file represents one skill, it may contain several intents which all belong together. Susi skills are stored in susi_skill_data repository. We can access any skill based on four tuples parameters model, group, language, skill.  For managing version control in skill data repository, the following dependency is added to build.gradle . JGit is a library which implements the Git functionality in Java.

dependencies {
 compile 'org.eclipse.jgit:org.eclipse.jgit:4.6.1.201703071140-r'
}

To implement our servlet we need to extend our servlet to AbstractAPIHandler. In Susi Server, an abstract class AbstractAPIHandler extending HttpServelets and implementing API handler interface is provided.

public class HistorySkillService extends AbstractAPIHandler implements APIHandler {}

The AbstractAPIHandler checks the permissions of the user using the userroles of and comparing it with the value minimum base role of each servlet. Thus to specify the user permission for a servlet we need Override the getMinimalBaseUserRole method.

 @Override
    public BaseUserRole getMinimalBaseUserRole() {
        return BaseUserRole.ANONYMOUS;
    }

UserRoles can be Admin, Privilege, User, Anonymous. In our case it is Anonymous. A User need not to log in to access this endpoint.

  @Override
    public String getAPIPath() {
        return "/cms/getSkillHistory.json";
    }

This methods sets the api endpoint path. One need to send requests at http://api.susi.ai/cms/getSkillHistory.json to get the modification history of skill. Next we will implement The ServiceImpl method where we will be processing the user request and giving back the service response.

@Override
    public ServiceResponse serviceImpl(Query call, HttpServletResponse response, Authorization rights, final JsonObjectWithDefault permissions) {

        String model_name = call.get("model", "general");
        File model = new File(DAO.model_watch_dir, model_name);
        String group_name = call.get("group", "knowledge");
        File group = new File(model, group_name);
        String language_name = call.get("language", "en");
        File language = new File(group, language_name);
        String skill_name = call.get("skill", "wikipedia");
        File skill = new File(language, skill_name + ".txt");
        JSONArray commitsArray;
        commitsArray = new JSONArray();
        String path = skill.getPath().replace(DAO.model_watch_dir.toString(), "models");
        //Add to git
        FileRepositoryBuilder builder = new FileRepositoryBuilder();
        Repository repository = null;
        try {
            repository = builder.setGitDir((DAO.susi_skill_repo))
                    .readEnvironment() // scan environment GIT_* variables
                    .findGitDir() // scan up the file system tree
                    .build();
            try (Git git = new Git(repository)) {
                Iterable<RevCommit> logs;
                logs = git.log().addPath(path).call();
                int i = 0;
                for (RevCommit rev : logs) {
                    commit = new JSONObject();
                    commit.put("commitRev", rev);
                    commit.put("commitName", rev.getName());
                    commit.put("commitID", rev.getId().getName());
                    commit.put("commit_message", rev.getShortMessage());
                    commit.put("author",rev.getAuthorIdent().getName());
                    commitsArray.put(i, commit);
                    i++;
                } success=true;
            } catch (GitAPIException e) {
                e.printStackTrace();
                success=false;
           } if(commitsArray.length()==0){
            success=false;
        }
        JSONObject result = new JSONObject();
        result.put("commits",commitsArray);
        result.put("success",success);
        return new ServiceResponse(result);
    }

To access any skill we need parameters model, group, language. We get this through call.get method where first parameter is the key for which we want to get the value and second parameter is the default value. Based on received model, group and language browse files in that folder we build the susi_skill_data repository path read the git variables and scan up the file system tree using FileRepositoryBuilder build() method. Next we fetch all the logs of the skill file and store them in json commits array and finally pass as a server response with success messages. In case of exceptions, pass service with success flags as false.

We have successfully implemented the servlet. Check the working of endpoint by sending request like http://api.susi.ai/cms/getSkillHistory.json?model=general&group=knowledge&language=en&skill=bitcoin and checking the response.

Susi skill cms uses this endpoint to fetch the skill history, try it out at http://skills.susi.ai/browseHistory

Resources

Communicate between Child and Parent Components in React JS of SUSI Web Chat

When we were developing SUSI AI web chat  some components became huge. So the team wanted to break some components into parts. Since the Login dialog-box is used in several  places we decided to make a separate component for Login Dialog-box. In this post I am discussing how we implemented the feature as a separate component and how we have changed the state of the parent component of the child component.

Login Dialog-box contains all the things of the login dialog-box component.

Child-component (Login Dialog-box component) is here:

This method executes the ‘switchDialog’ function of the parent component.

export default class LoginDialog extends React.Component {

   handleClose = () => {
      this.props.switchDialog(false);
   };

   render() {
       this.state = { open: this.props.open }
       const actions = <RaisedButton
           label="Cancel"
           backgroundColor={
               UserPreferencesStore.getTheme() === 'light' ? '#607D8B' : '#19314B'}
           labelColor="#fff"
           width='200px'
           keyboardFocused={true}
           onTouchTap={this.handleClose}
       />;

       return (
           <Dialog
               actions={actions}
               modal={false}
               open={this.props.open}
               autoScrollBodyContent={true}
               bodyStyle={bodyStyle}
               contentStyle={{ width: '35%', minWidth: '300px' }}
               onRequestClose={this.handleClose}>
               <Login {...this.props} />
           </Dialog>
       );
   }

};

In this part we validate property types that has passed from the parent component.

LoginDialog.propTypes = {
   open: PropTypes.bool,
   switchDialog: PropTypes.func
};

In render() method I have returned the element.
To open and close dialog we have to communicate with parent component. We can send an instruction as an attribute of the element and we can refer it inside the element as “props”. This is how I have sent an instruction to the child element.
Parent-component:
‘handleOpen’ function opens the dialog when user hit on the login button.

   handleOpen = () => {
       this.setState({ open: true });
   };

‘switchDialog’ function is using for change the state of parent component from child Component (Login Dialog-box component).

   switchDialog=(dialogState)=>{
       this.setState({open:dialogState});
   };

   render() {

       const styles = {
           'margin': '60px auto',
           'width': '100%',
           'padding': '20px',
           'textAlign': 'center'
       }

       return (
           <div className="signUpForm">
               <Paper zDepth={1} style={styles}>
                   <h1>Sign Up with SUSI</h1>
                   <form onSubmit={this.handleSubmit}>
                       <div>
                           <h4>If you have an Account Please Login</h4>
                           <RaisedButton
                               onTouchTap={this.handleOpen}
                               label='Login'
                               backgroundColor={
                                   UserPreferencesStore.getTheme()==='light'
                                   ? '#607D8B' : '#19314B'}
                               labelColor="#fff" />
                       </div>
                   </form>
               </Paper>

               <LoginDialog {...this.props} open={this.state.open} switchDialog={this.switchDialog} />
           </div>
       );
   };

To open and close the dialog-box we have to send the state of the parent component to child component. To close the dialog-box we have to update the parent component’s state from child component.

To change the parent component’s state we have used this in element.

switchDialog={this.switchDialog}

To send the state to the child component we used this.

open={this.state.open}

To send other properties to the element we used this.

{...this.props}

After closing the dialog-box it calls this method and it updates the state of the parent component.

handleClose = () => {
      this.props.switchDialog(false);
};

This is how we can communicate between child and parent components using react.

Resources:

Component Communication: http://andrewhfarmer.com/component-communication/
Material UI Dialogs: http://www.material-ui.com/#/components/dialog

Using CoreLocation in SUSI iOS

The SUSI Server responds with intelligent answers to the user’s queries. To make these answers better, the server makes use of the user’s location which is sent as a parameter to the query request each time. To implement this feature in the SUSI iOS client, we use the CoreLocation framework provided by Apple which helps us to get the user’s location coordinates and add them as a parameter to each request made.

In order to start with using the CoreLocation framework, we first import it inside the view controller.

import CoreLocation

Now, we create a variable of type CLLocationManager which will help us to use the actual functionality.

// Location Manager
var locationManager = CLLocationManager()

The location manager has some delegate methods which give an option to get the maximum accuracy for a user’s location.  To set that, we need the controller to conform to the CLLocationManagerDelegate, so we create an extension of the view controller conforming to this.

extension MainViewController: CLLocationManagerDelegate {

   // use functionality

}

Next, we set the manager delegate.

locationManager.delegate = self

And create a method to ask for using the user’s location and set the delegate properties.

func configureLocationManager() {
       locationManager.delegate = self
       if CLLocationManager.authorizationStatus() == .notDetermined || CLLocationManager.authorizationStatus() == .denied {
           self.locationManager.requestWhenInUseAuthorization()
       }

       locationManager.distanceFilter = kCLDistanceFilterNone
       locationManager.desiredAccuracy = kCLLocationAccuracyBest
}

Here, we ask for the user location if it was previously denied or is not yet determined and following that, we set the `distanceFilter` as kCLDistanceFilterNone  and `desiredAccuray` as kCLLocationAccuracyBest.. Finally, we are left with starting to update the location which we do by:

locationManager.startUpdatingLocation()

We call this method inside viewDidLoad to start updation of the location when the view first loads. The complete extension looks like below:

extension MainViewController: CLLocationManagerDelegate {

   // Configures Location Manager
   func configureLocationManager() {
       locationManager.delegate = self
       if CLLocationManager.authorizationStatus() == .notDetermined || CLLocationManager.authorizationStatus() == .denied {
           self.locationManager.requestWhenInUseAuthorization()
       }

       locationManager.distanceFilter = kCLDistanceFilterNone
       locationManager.desiredAccuracy = kCLLocationAccuracyBest
       locationManager.startUpdatingLocation()
   }

}

Now, it’s very easy to use the location manager and get the coordinates and add it to the params for each request.

if let location = locationManager.location {
   params[Client.ChatKeys.Latitude] = location.coordinate.latitude as AnyObject
   params[Client.ChatKeys.Longitude] = location.coordinate.longitude as AnyObject
}

Now the params which is a dictionary object is added to each request made so that the user get’s the most accurate results for each query he makes.

References:

Using Vector Images in SUSI Android

SUSI is an artificial intelligence for interactive chat bots. For making it more user friendly and interactive we add a lot of images in the form of drawable resources in the SUSI Android App (https://github.com/fossasia/susi_android). Most of these drawables are in the form of PNGs. There are certain problems associated with the use of PNG images.

  1. PNGs cannot be scaled without losing quality. Due to which for the same PNG image we have to include separate images of varied quality. Otherwise the image will become blur.
  2. PNGs tends to take large disk space which can be easily reduced with the use of vector images.
  3. PNGs have fixed color and dimensions which cannot be changed.

Due to the above shortcomings of PNG images we decided to use vector drawable images instead of them.

Advantages associated with Vector images

  1. They can be scaled to any size without the loss in quality. Thus we need to include only a single image in the app and not of varied qualities.
  2. They are very small in size as compared to PNGs.
  3. They can be easily modified programmatically in XML file unlike PNGs.

Using Vector Images in Android Studio

Android Studio provide tools by which we can directly import vector drawables in the project. To import Vector images go to File>New>Vector Assets in studio.

From here we can choose the icon we want to include in our project and click OK. The icon will appear in the drawables directory and can be used anywhere in the projects.

Implementation in SUSI Android

In Susi Android we have used various vector images such as arrows, pointer and even the logo of the app. Here below is the logo of SUSI.

This is actually a vector image below we will see the code required to get this logo as the output.

<vector android:height="50dp" android:viewportHeight="279.37604"

  android:viewportWidth="1365.2" android:width="220dp" xmlns:android="http://schemas.android.com/apk/res/android">

<path android:fillColor="#ffffff"

      android:pathData="M127.5,7.7c-26.8,3.3 -54.2,16.8 -75.9,37.4 -11.8,11.1 -20.4,22.9 -28.1,38.4 -8.9,17.8 -12.8,32.1 -13.7,51l-0.3,6 39,0 39,0 0.3,-4c0.7,-12.1 6.8,-24.1 17.2,-34.5 8.5,-8.4 16.2,-13.4 25.9,-16.7l6.6,-2.2 81.3,-0.1 81.2,0 0,-38 0,-38 -84.7,0.1c-46.7,0.1 -86.1,0.4 -87.8,0.6z" android:strokeColor="#00000000"/>

  <path android:fillColor="#ffffff"

      android:pathData="M319.2,11.3l-4.3,4.3 0.3,103c0.4,113.2 0,105.9 6.4,118.6 10.8,21.3 35.1,41.9 56.2,47.3 8.5,2.3 99.1,2.2 107.7,0 18.7,-4.9 39.2,-20.7 51.5,-39.7 3.4,-5.1 7.1,-12.2 8.3,-15.8l2.2,-6.5 0.5,-103.3 0.5,-103.3 -4.5,-4.4 -4.6,-4.5 -31.5,0 -31.5,0 -4.7,4.8 -4.7,4.8 0,93 0,93 -3.3,3.2 -3.3,3.2 -29,0 -29,0 -2.6,-2.7 -2.7,-2.8 -0.7,-94.2 -0.7,-94.2 -4.3,-4 -4.2,-4.1 -31.9,0 -31.9,0 -4.2,4.3z" android:strokeColor="#00000000"/>

  <path android:fillColor="#ffffff"

      android:pathData="M680,7.6c-31.6,4.8 -56.1,17.3 -79,40.3 -23.2,23.3 -36.3,50.5 -38.9,80.9 -0.5,5.9 -0.7,11 -0.4,11.4 0.2,0.5 17.7,0.8 38.8,0.8l38.4,0 0.6,-4.8c3.2,-23.2 21.3,-44.1 44.7,-51.3 5.6,-1.8 10.6,-1.9 86.6,-1.9l80.7,0 -0.3,-38 -0.2,-38 -84.3,0.1c-46.3,0.1 -85.3,0.3 -86.7,0.5z" android:strokeColor="#00000000"/>

  <path android:fillColor="#ffffff"

      android:pathData="M869.1,13.4l-4.1,6.4 0,126.4 0,126.3 4.8,6.7 4.7,6.8 31.6,0 31.6,0 4.7,-7 4.6,-7 0,-125.7 0,-125.8 -4.7,-6.7 -4.8,-6.8 -32.1,0 -32.1,0 -4.2,6.4z" android:strokeColor="#00000000"/>

  <path android:fillColor="#ffffff"

      android:pathData="M222.5,152.2c-0.2,0.7 -0.9,4.2 -1.5,7.7 -3.4,19.5 -19.4,38 -40,46.4l-5.5,2.2 -83,0.5 -83,0.5 -0.3,37.8 -0.2,37.8 89.2,-0.3 89.3,-0.3 9.6,-2.7c57.7,-16.3 100.1,-67.4 102.1,-123.3l0.3,-7 -38.3,-0.3c-30.1,-0.2 -38.3,0 -38.7,1z" android:strokeColor="#00000000"/>

  <path android:fillColor="#ffffff"

      android:pathData="M774.5,152.2c-0.2,0.7 -0.9,4.1 -1.5,7.5 -3.3,19.2 -18.8,37.3 -39.4,46.2l-6.1,2.6 -83,0.5 -83,0.5 -0.3,37.7 -0.2,37.8 85.9,0c93.7,0 91.4,0.1 110.1,-5.9 26.4,-8.5 53.3,-28.4 69.8,-51.7 15.2,-21.3 25.1,-50.1 24,-69.9l-0.3,-6 -37.8,-0.3c-29.7,-0.2 -37.8,0 -38.2,1z" android:strokeColor="#00000000"/>

  <path android:fillColor="#ffffff" android:pathData="m1146.99,0 l-1.38,1.19c-0.76,0.66 -1.85,1.61 -2.43,2.13 -0.58,0.51 -1.75,1.54 -2.61,2.28 -1.52,1.31 -1.58,1.41 -2.4,3.53 -0.46,1.2 -0.92,2.37 -1.01,2.59 -30.55,82.93 -61.62,165.72 -96.03,259.63 0,0.08 1.61,1.88 3.57,3.98l3.57,3.84 33.47,-0.04 33.47,-0.04c12.28,-35.6 25.13,-72.47 37.4,-107.27 0.06,-0.25 0.28,-0.64 0.5,-0.88 0.37,-0.41 0.61,-0.43 4.2,-0.43 3.63,0 3.83,0.02"/>

  <path android:fillColor="#ffffff" android:pathData="m967.09,279.18c-2.48,-3.74 -4.97,-7.04 -8.09,-11.76l0.09,-43.92c3.34,-5.26 5.31,-6.73 8.42,-11.51 17.91,0.02 34.3,0.26 50.88,0.26 3.21,4.88 4.09,6.72 7.81,12.66 -0.05,13.98 0.1,27.96 -0.12,41.94 -2.9,4.2 -4.27,7.42 -7.78,12.18 -18.81,-0.04 -35.43,0.2 -51.21,0.15z"/>

  <path android:fillColor="#ffffff"

      android:pathData="m1287.3,6.59 l-4.1,6.4 0,126.4 0,126.3 4.8,6.7 4.7,6.8 31.6,0 31.6,0 4.7,-7 4.6,-7 0,-125.7 0,-125.8 -4.7,-6.7 -4.8,-6.8 -32.1,0 -32.1,0 -4.2,6.4z" android:strokeColor="#00000000"/>


</vector>

In this code we can easily change the color and minor details for the logo which could have been not possible if the logo was in PNG format. Also we don’t need multiple logo images of varied qualities as it can be scaled without decreasing quality.

Resources

Using SUSI AI Server to Store User Feedback for a Skill

User feedback is valuable information that plays an important  role in improving the quality of service. In SUSI AI server we are planning to make a feedback mechanism to see if the user liked the answer or not. The result of that user input (which can be given using a vote button) will be then learned to enhance the future use of the rule. So as a first step for implementation of  skill rating system with guided learning, we need to store the user rating of a skill . In this blogpost we will learn how to make an endpoint for getting skill rating from user. This API endpoint will be used  by its web and mobile clients.
Before the implementation of API  let’s look how data is stored in SUSI AI Susi_server uses DAO in which skill rating is stored as JSONTray. 

 public JsonTray(File file_persistent, File file_volatile, int cachesize) throws IOException {
        this.per = new JsonFile(file_persistent);
        this.vol = new CacheMap<String, JSONObject>(cachesize);
        this.file_volatile = file_volatile;
        if (file_volatile != null && file_volatile.exists()) try {
            JSONObject j = JsonFile.readJson(file_volatile);
            for (String key: j.keySet()) this.vol.put(key, j.getJSONObject(key));
        } catch (IOException e) {
            e.printStackTrace();
        }
    }

JsonTray takes three parameters the persistent file, volatile file and cache size to store them as cache map in String and JsonObject pairs. The HttpServlet class which provides methods, such as doGet and doPost, for handling HTTP-specific services.In Susi Server an abstract class AbstractAPIHandler extending HttpServelets and implementing API handler interface is provided. Next we will inherit our RateSkillService class from AbstractAPIHandler and implement APIhandler interface.

public class RateSkillService extends AbstractAPIHandler implements APIHandler {
    private static final long serialVersionUID =7947060716231250102L;
    @Override
    public BaseUserRole getMinimalBaseUserRole() {
        return BaseUserRole.ANONYMOUS;
    }

    @Override
    public JSONObject getDefaultPermissions(BaseUserRole baseUserRole) {
        return null;
    }

    @Override
    public String getAPIPath() {
        return "/cms/rateSkill.json";
    }

}

The getMinimalBaseRole method tells the minimum Userrole required to access this servlet it can also be ADMIN, USER. In our case it is Anonymous. A User need not to log in to access this endpoint. The getAPIPath() methods sets the API endpoint path, it gets appended to base path which is 127.0.0.1:4000/cms/rateSkill.json for local host .

Next we will implement serviceImpl method

  @Override
    public ServiceResponse serviceImpl(Query call, HttpServletResponse response, Authorization rights, final JsonObjectWithDefault permissions) {

        String model_name = call.get("model", "general");
        File model = new File(DAO.model_watch_dir, model_name);
        String group_name = call.get("group", "knowledge");
        File group = new File(model, group_name);
        String language_name = call.get("language", "en");
        File language = new File(group, language_name);
        String skill_name = call.get("skill", null);
        File skill = new File(language, skill_name + ".txt");
        String skill_rate = call.get("rating", null);

        JSONObject result = new JSONObject();
        result.put("accepted", false);
        if (!skill.exists()) {
            result.put("message", "skill does not exist");
            return new ServiceResponse(result);

        }
        JsonTray skillRating = DAO.skillRating;
        JSONObject modelName = new JSONObject();
        JSONObject groupName = new JSONObject();
        JSONObject languageName = new JSONObject();
        if (skillRating.has(model_name)) {
            modelName = skillRating.getJSONObject(model_name);
            if (modelName.has(group_name)) {
                groupName = modelName.getJSONObject(group_name);
                if (groupName.has(language_name)) {
                    languageName = groupName.getJSONObject(language_name);
                    if (languageName.has(skill_name)) {
                        JSONObject skillName = languageName.getJSONObject(skill_name);
                        skillName.put(skill_rate, skillName.getInt(skill_rate) + 1 + "");
                        languageName.put(skill_name, skillName);
                        groupName.put(language_name, languageName);
                        modelName.put(group_name, groupName);
                        skillRating.put(model_name, modelName, true);
                        result.put("accepted", true);
                        result.put("message", "Skill ratings updated");
                        return new ServiceResponse(result);
                    }
                }
            }
        }
        languageName.put(skill_name, createRatingObject(skill_rate));
        groupName.put(language_name, languageName);
        modelName.put(group_name, groupName);
        skillRating.put(model_name, modelName, true);
        result.put("accepted", true);
        result.put("message", "Skill ratings added");
        return new ServiceResponse(result);

    }

    /* Utility function*/
    public JSONObject createRatingObject(String skill_rate) {
        JSONObject skillName = new JSONObject();
        skillName.put("positive", "0");
        skillName.put("negative", "0");
        skillName.put(skill_rate, skillName.getInt(skill_rate) + 1 + "");
        return skillName;
    }

 

One can access any skill based on four tuples parameters model, group, language, skill. Before rating a skill we must ensure whether it exists or not. We can get the required parameters through call.get() method where first parameter is the key for which we want to get the value and second parameter is the default value. If skill.exists() method return false we generate error message stating “No such skill exists”. Otherwise check if the skill exist in our skillRating.json file if so, update the current ratings otherwise create a new json object and add it to rating file based on model, group and language. After successful implementation go ahead and test your endpoint on http://localhost:4000/cms/rateSkill.json?model=general&group=knowledge&skill=who&rating=positive

You can also check for the updated json file in  susi_server/data/skill_rating/skillRating.json 

{"general": {
 "assistants": {"en": {
   "language_translation": {
     "negative": "1",
     "positive": "0"
  }}},
 "smalltalk": {"en": {
   "aboutsusi": {
   "negative": "0",
   "positive": "1"
 }}},
 "knowledge": {"en": {
   "who": {
     "negative": "2",
     "positive": "4"
   }}}
}}

And if the skill is not present if will generate error message

We have successfully implemented the API endpoint for storing the user skill’s feedback. For more information take a look at Susi server and join gitter chat channel for discussions.

Resources 

Auto deployment of SUSI Skill CMS on gh pages

Susi Skill CMS is a web application framework to edit susi skills. It is currently in development stage, hosted on http://skills.susi.ai. It is built using ReactJS . In this blogpost we will see how to automatically deploy the repository on gh pages.
Setting up the project
Fork susi_skill_cms repository and clone it to your desktop, make sure you have node and npm versions greater than 6 and 3 respectively. Next go to cloned folder and install all the dependencies by running :

:$ npm install

Next run on http://localhost:3000 by running the command

:$ npm run start

To auto deploy changes on gh-pages branch, we need to setup Travis for the project. Register yourself on https://travis-ci.org/ and turn on the Travis for this repository. Next add .travis.yml in the root directory of the source folder.  

sudo: required
dist: trusty
language: node_js
node_js:
  - 6

before_install:
  - export CHROME_BIN=chromium-browser
  - export DISPLAY=:99.0
  - sh -e /etc/init.d/xvfb start

before_script:
  - npm run build

script:
  - npm run test

after_success:
  - bash ./deploy.sh

cache:
  directories: node_modules

# safelist
branches:
  only:
  - master 

Source: https://github.com/fossasia/susi_skill_cms/blob/master/.travis.yml

The travis configuration files will ensure that the project is building for every changes made, using npm run test command, in our case it will only consider changes made on master branch , if you want to watch other branches to add the respective branch name in travis configurations. After checking for build passing we need to automatically push the changes made for which we will use a bash script.

#!/bin/bash

SOURCE_BRANCH="master"
TARGET_BRANCH="gh-pages"

# Pull requests and commits to other branches shouldn't try to deploy.
if [ "$TRAVIS_PULL_REQUEST" != "false" -o "$TRAVIS_BRANCH" != "$SOURCE_BRANCH" ]; then
    echo "Skipping deploy; The request or commit is not on master"
    exit 0
fi

# Save some useful information
REPO=`git config remote.origin.url`
SSH_REPO=${REPO/https:\/\/github.com\[email protected]:}
SHA=`git rev-parse --verify HEAD`

ENCRYPTED_KEY_VAR="encrypted_${ENCRYPTION_LABEL}_key"
ENCRYPTED_IV_VAR="encrypted_${ENCRYPTION_LABEL}_iv"
ENCRYPTED_KEY=${!ENCRYPTED_KEY_VAR}
ENCRYPTED_IV=${!ENCRYPTED_IV_VAR}
openssl aes-256-cbc -K $encrypted_2662bc12c918_key -iv $encrypted_2662bc12c918_iv -in deploy_key.enc -out ../deploy_key -d
chmod 600 ../deploy_key
eval `ssh-agent -s`
ssh-add ../deploy_key

# Cloning the repository to repo/ directory,
# Creating gh-pages branch if it doesn't exists else moving to that branch
git clone $REPO repo
cd repo
git checkout $TARGET_BRANCH || git checkout --orphan $TARGET_BRANCH
cd ..

# Setting up the username and email.
git config user.name "Travis CI"
git config user.email "$COMMIT_AUTHOR_EMAIL"

# Cleaning up the old repo's gh-pages branch except CNAME file and 404.html
find repo/* ! -name "CNAME" ! -name "404.html" -maxdepth 1  -exec rm -rf {} \; 2> /dev/null
cd repo

git add --all
git commit -m "Travis CI Clean Deploy : ${SHA}"

git checkout $SOURCE_BRANCH

# Actual building and setup of current push or PR.
npm install
npm run build
mv build ../build/

git checkout $TARGET_BRANCH
rm -rf node_modules/
mv ../build/* .
cp index.html 404.html

# Staging the new build for commit; and then committing the latest build
git add -A
git commit --amend --no-edit --allow-empty

# Deploying only if the build has changed
if [ -z `git diff --name-only HEAD HEAD~1` ]; then

  echo "No Changes in the Build; exiting"
  exit 0

else
  # There are changes in the Build; push the changes to gh-pages
  echo "There are changes in the Build; pushing the changes to gh-pages"

  # Actual push to gh-pages branch via Travis
  git push --force $SSH_REPO $TARGET_BRANCH
fi

Source : Bash script for automatic deployment

This bash script will enable travis ci user to push changes to gh pages, for this we need to store the credentials of the repository in encrypted form. To get the public/ private rsa keys use the following command

ssh-keygen -t rsa -b 4096 -C "[email protected]"

It will generate keys in .ssh/id_rsa folder in your home repository.

Make sure you do not enter any passphrase while generating credentials otherwise travis will get stuck at time of decrypting the keys. Copy the public key and deploy the key to repository by visiting  https://github.com/<your name>/<your repo>/settings/keys


Next install travis for encryption of keys.

sudo apt install ruby ruby-dev
sudo gem install travis

Encrypt your private deploy_key and add it to root of your repository using command

travis encrypt-file deploy_key

After successful encryption, you will see a message

Please add the following to your build script (before_install stage in your .travis.yml, for instance):

openssl aes-256-cbc -K $encrypted_2662bc12c918_key -iv $encrypted_2662bc12c918_iv -in deploy_key.enc -out ../deploy_key -d

Add the above generated script in travis and push the changes on your master branch. Do not push the deploy_key only the encryption file deploy_key.enc
Finally, add the deploy link of gh pages in package.json of your using key “homepage”.

 "homepage": "http://skills.susi.ai/"

And in scripts of package.json add

"deploy": "gh-pages -d build",

Commit and push your changes and from now onward all your changes will be automatically pushed to gh pages branch. For contribution visit Susi_Skill_CMS.

Resources

How SUSI Analyzes A Given Response

Ever wondered where SUSI’s answers come from? Now Susi has ability to do an answer analysis. To get that analysis, just ask susi “analysis”. This will set susi into an analysis mode, will tell where the latest answer came from and will give you the link for improving the skill.

Let’s check out how Susi analysis work. The skill for analysis is defined  en_0001_foundation.txt  as following

analysis|analyse|analyze|* analysis|* analyse|* analyze|analysis *|analyse *|analyze *
My previous answer is defined in the skill $skill$. You can help to improve this skill and <a href="$skill_link$" target="_blank"> edit it in the code repository here.</a>

$skill$ and $skill_link$ are the variable compiled using

public static final Pattern variable_pattern = Pattern.compile("\\$.*?\\$");

These variables are memorized in Susi cognition. A cognition is the combination of a query of a user with the response of susi.

SusiThought dispute = new SusiThought();
List<String> skills = clonedThought.getSkills();
 if (skills.size() > 0) {
    dispute.addObservation("skill", skills.get(0));
    dispute.addObservation("skill_link",getSkillLink(skills.get(0)));
   }

Susi Thought is a piece of data that can be remembered. The structure of the thought is modeled as a table in which information contained in it is organized in rows and columns.

 public SusiThought addObservation(String featureName, String observation) ;

One can memorize using addObservation() method.  It takes two parameter featureName the object key and observation the object value. It is a table of information pieces as a set of rows which all have the same column names. It inserts the new data always in front of existing similar data rather than overwriting them.

 public String getSkillLink(String skillPath) {
       String link=skillPath;
        if(skillPath.startsWith("/susi_server")) {
            link ="https://github.com/fossasia/susi_server/blob/development" + skillPath.substring("/susi_server".length());
        } else if (skillPath.startsWith("/susi_skill_data")) {
            link = "https://github.com/fossasia/susi_skill_data/blob/master" + skillPath.substring("/susi_skill_data".length());
        }
        return link;
    }

The getSkillLink is a utitlity method to return the link of the skill source github repository based on skillPath.

private String skill;
SusiThought recall;
final SusiArgument flow = new SusiArgument().think(recall);
this.skill = origin.getAbsolutePath();
 if (this.skill != null && this.skill.length() > 0) flow.addSkill(this.skill);

The source of the skill gets added in SusiIntent.java using getAbsolutePath() method which resolves the skill path in the filesystem. Intent  considers the key from the user query, matches the intent tokens to get the optimum result and produces json like

 "data": [
      {
        "object": "If you spend too much time thinking about a thing, you'll never get it done.",
        "0": "tell me a quote",
        "token_original": "quote",
        "token_canonical": "quote",
        "token_categorized": "quote",
        "timezoneOffset": "-330",
        "answer": "When you discover your mission, you will feel its demand. It will fill you with enthusiasm and a burning desire to get to work on it. ",
        "skill_link": "https://github.com/fossasia/susi_skill_data/blob/master/models/general/entertainment/en/quotes.txt",
        "query": "tell me a quote",
        "skill": "/susi_skill_data/models/general/entertainment/en/quotes.txt"
      },

The getskills() method returns list of skill from json which are later added for memorization.

    public List<String> getSkills() {
        List<String> skills = new ArrayList<>();
        getSkillsJSON().forEach(skill -> skills.add((String) skill));
        return skills;
    }

This is how Susi is able to fetch  where the answer came from. Next time when you have a chat with susi do check skill analysis and add your ideas to improve the skill. Take a look at Susi_skill_data for more skills and  read this tutorial  for creating skills for susi.

Resources

Using react-slick for Populating RSS Feeds in SUSI Chat

To populate SUSI RSS Feed generated, while chatting on SUSI Web Chat, I needed a Horizontal Swipeable Tile Slider. For this purpose, I made use of the package react-slick. The information which was supposed to be handled as obtained from the SUSI Server to populate the RSS feed was

  • Title
  • Description
  • Link

Hence to show all of this information like a horizontal scrollable feed, tiles by react-slick solves the purpose. To achieve the same, let’s see follow the steps below.

  1. First step is to install the react-slick package into our project folder, for that we use
npm install react-slick --save
  1. Next we import the Slider component from react-slick package into the file where we want the slider, here MessageListItem.react.js
import Slider from 'react-slick'
  1. Add Slider with settings as given in the docs. This is totally customisable. For more customisable options go to https://github.com/akiran/react-slick
var settings = {
         speed: 500,
         slidesToShow: 3,
         slidesToScroll: 1,
        swipeToSlide:true,
         swipe:true,
         arrows:false
     };

speed – The Slider will scroll horizontally with this speed.

slidesToShow – The number of slides to populate in one visible screen

swipeToSlide, swipe – Enable swiping on touch screen devices.

arrows – Put false, to disable arrows

  1. The next step is to initialize the Slider component inside the render function and populate it with the tiles. The full code snippet is available at MessageListItem.react.js
<Slider {..settings}>//Append the settings which you created
    {yourListToProps} // Add the list tiles you want to see
</Slider>
  1. Adding a little bit of styling, full code available in ChatApp.css
 .slick-slide{
 margin: 0 10px;
}
.slick-list{
  max-height: 100px;
}
  1. This is the output you would get in your screen.

  • Note – To prevent errors like the following on testing with jest, you will have to add the following lines into the code.

Error log, which one may encounter while using react-slick –

 matchMedia not present, legacy browsers require a polyfill

  at Object.MediaQueryDispatch (node_modules/enquire.js/dist/enquire.js:226:19)
  at node_modules/enquire.js/dist/enquire.js:291:9
  at i (node_modules/enquire.js/dist/enquire.js:11:20)
  at Object.<anonymous> (node_modules/enquire.js/dist/enquire.js:21:2)
  at Object.<anonymous> (node_modules/react-responsive-mixin/index.js:2:28)
  at Object.<anonymous> (node_modules/react-slick/lib/slider.js:19:29)
  at Object.<anonymous> (node_modules/react-slick/lib/index.js:3:18)
  at Object.<anonymous> (src/components/Testimonials.jsx:3:45)
  at Object.<anonymous> (src/pages/Index.jsx:7:47)
  at Object.<anonymous> (src/App.jsx:8:40)
  at Object.<anonymous> (src/App.test.jsx:3:38)
  at process._tickCallback (internal/process/next_tick.js:103:7)

In package.json, add the following lines-

"peerDependencies": {
      "react": "^0.14.0 || ^15.0.1",
      "react-dom": "^0.14.0 || ^15.0.1"
    },
   "jest": {
      "setupFiles": ["./src/setupTests.js", "./src/node_modules/react-scripts/config/polyfills.js"]
   },

In src/setupTests.js, add the following lines.

window.matchMedia = window.matchMedia || (() => { return { matches: false, addListener: () => {}, removeListener: () => {}, }; });

These lines will help resolve any occurring errors while testing with Jest or ESLint.

To have a look at the full project, visit https://github.com/fossasia/chat.susi.ai and feel free to contribute. To test the project visit http://chat.susi.ai

Resources

 

Implementing Login Functionality in SUSI Web Chat

SUSI Web Chat is fully equipped with all the accounting features which are being provided by the SUSI.AI API. This blog discloses all the API features one needs to know to embed the Login functionality in SUSI Web Chat.

  1. To embed the Login feature, first we create a form using material-ui.com components with the followng fields
    1. Email
    2. Password
    3. Note: We can also chose a Custom Server while logging in, here I have used the Standard Server ie. http://api.susi.ai to make the user Login

The form can be made with the help of the following fields

  • TextField for Email, props to be passed
    • Name – email
    • Value – this.state.email which gets the value of the current email
    • floatingLabelText is Email,
    • errorText is the message which we want to show when the email does not match the regex or its empty.

Code Snippet –

<TextField name="email" value={this.state.email} onChange={this.handleChange} errorText={this.emailErrorMessage}    floatingLabelText="Email" />
  • PasswordField for Password
    • Name – password
    • Value – this.state.password which gets the value of the current email
    • floatingLabelText is Password,
    • errorText is the message which we want to show when the password is not filled.

Code Snippet-

<PasswordField name='password' value={this.state.password} onChange={this.handleChange} errorText={this.passwordErrorMessage}   floatingLabelText='Password' />
  • The next elements are RadioButton groups taken from material-ui.com. This ensures the user signs into a standard server or even to a custom server. This is not compulsory as of now.
  • And lastly we need a submit button, which is disabled until all the fields are filled.

Code Snippet –

<RaisedButton label="Login" type="submit" labelColor="#fff" disable={!this.state.validForm} />

For the full form, check out this file at Login.react.js

  1. A Sample UI could be as shown in the image
  2. Next after creating the Login Screen, we make the onSubmit prop which is to be hooked up with another function called handleSubmit. An example code snippet from Login.react.js
 handleSubmit = (e) => {
        e.preventDefault();
        // Get the trimmed values from the fields
        var email = this.state.email.trim();
        var password = this.state.password.trim();
        // Set the default server to login
        let BASE_URL = defaults.Server;
            // handle all the details of the chosen server
        let serverUrl = this.state.serverUrl;
        if(serverUrl.slice(-1) === '/'){
            serverUrl = serverUrl.slice(0,-1);
        }
        if(serverUrl !== ''){
            BASE_URL = serverUrl;
        }
// if email and password is filled return true
        if (!email || !password) { return this.state.isFilled; }
// Check the regex of email
        let validEmail = /^[A-Z0-9._%+-]+@[A-Z0-9.-]+\.[A-Z]{2,4}$/i.test(email); 
// Pass the parameters to the loginEndPoint
        let loginEndPoint =
            BASE_URL+'/aaa/login.json?type=access-token&login=' +
            this.state.email + '&password=' + this.state.password;
        // If email and password is filled and valid call AJAX
        if (email && validEmail) {
            // AJAX Calls
        }
    }
    1. Then we make the Ajax Calls and store the created token from hitting the URL at http://api.susi.ai/aaa/login.json?type=access-token&login=EMAIL&password=PASSWORD. We store the cookie in browser and generate a session for the user using a package ‘universal-cookies’.
$.ajax({
    url: loginEndPoint,
    dataType: 'jsonp',
    jsonpCallback: 'p',
    jsonp: 'callback',
    crossDomain: true,
    success: function (response) {
        cookies.set('serverUrl', BASE_URL, { path: '/' });
        let accessToken = response.access_token;
        let state = this.state;// Adding the current State
        let time = response.valid_seconds; // Get the valid time of the cookie
        state.isFilled = true; // Set isFilled to true
        state.accessToken = accessToken; // Get the token
        state.success = true; // Set Success to true
        state.msg = response.message; // Get the server message
        state.time = time; // Get the time in the state
        this.setState(state); // Set the  state with the values
/* Pass the token to the binding function handleOnSubmit passing the arguments - token and the valid time */
        this.handleOnSubmit(accessToken, time);
    }.bind(this),
    error: function (errorThrown) {
        let msg = 'Login Failed. Try Again';
        let state = this.state;
        state.msg = msg;
        this.setState(state);
    }.bind(this)
});

 

    1. We then fire up the handleOnSubmit(accessToken, time) which saves the token for the given expiration time from the server.

Here’s the sample code

handleOnSubmit = (loggedIn, time) => {
        let state = this.state;
        if (state.success) {
            cookies.set('loggedIn', loggedIn, { path: '/', maxAge: time }); // set the cookie in the browser to maintain the loggedIn state
            this.props.history.push('/', { showLogin: false });
            window.location.reload();// reload after the loggedIn cookie creation
        }
        else {
            this.setState({
                error: true,
                accessToken: '',
                success: false
            });
        }
    }
  1. We then check the access token and redirect him based on his login state. This is handled in MessageSection.react.js
import Cookies from 'universal-cookie';
const cookies = new Cookies();
if (cookies.get('loggedIn')) {
    //Show all functionalities of loggedIn state
}
else {
//Redirect user to login page
}

 

To have a look at the full project, visit https://github.com/fossasia/chat.susi.ai and feel free to contribute. To test the project visit http://chat.susi.ai

Resources