Implementing Skill Listing in SUSI iOS

Skills are basically a set of rules which respond to the user’s queries through any client app. All the skills are defined in the SUSI Skill Data repo where the user’s queries are matched with the already present skills and the server responds accordingly. Apps like Alexa, Google Assistant have an interface to view skills with a set of sample queries that can be used therefore, we are adding the same skill display UI in the SUSI iOS app.

Implementation

All the skills are arranged into categories or groups, so we first need to fetch all those groups followed by fetching skills from each group. For listing all the groups, we use the endpoint below:

http://api.susi.ai/cms/getGroups.json

Which returns all the groups in the groups object like below:

{
  "session": {"identity": {
    "type": "host",
    "name": "67.214.191.117",
    "anonymous": true
  }},
  "accepted": true,
  "groups": [
    "Social",
    "News",
    "Food and Drink",
    "Travel and Transportation",
    "Connected Car",
    "Movies and TV",
    "Problem Solving",
    "Knowledge",
    "Business and Finance",
    "Productivity",
    "Games, Trivia and Accessories",
    "Lifestyle",
    "Health and Fitness",
    "Music and Audio",
    "Shopping",
    "Communication",
    "Novelty and Humour",
    "Utilities",
    "Sports", 
    "Weather"
  ],
  "message": "Success: Fetched group list"
}

After the groups have been fetched, we need to get the skills for each group. Here, we use the endpoint below:

http://api.susi.ai/cms/getSkillList.json?group=GROUP_NAME

Since, we have a number of groups, we need to make the above API call as many times as the group count is. A sample call would look like:

http://api.susi.ai/cms/getSkillList.json?group=News

which would fetch all the skills in the News group.

{
  "accepted": true,
  "model": "general",
  "group": "News",
  "language": "en",
  "skills": {"news": {
    "image": "images/news.png",
    "author_url": "https://github.com/AliAyub007",
    "examples": [
      "News",
      "latest news",
      "most viewed articles in science today",
      "most viewed articles in science in the last week",
      "most viewed articles in science in the last month",
      "most shared articles in science today",
      "can you tell me last week's most shared articles in science",
      "do you know most shared articles in arts in the last month",
      "most emailed articles today in arts",
      "most emailed articles in science in the last week",
      "can you tell me most emailed articles in science in the last month",
      "articles in science",
      "show me articles",
      "most emailed articles",
      "most shared articles",
      "tell me news in tech world"
    ],
    "developer_privacy_policy": null,
    "author": "Ali Ayub Khan",
    "skill_name": "NEWS",
    "dynamic_content": true,
    "terms_of_use": null,
    "descriptions": "A skill to give news.",
    "skill_rating": null
  }},
  "message": "Success: Fetched skill list",
  "session": {"identity": {
    "type": "host",
    "name": "23.94.137.239",
    "anonymous": true
  }}
}

Each such json object gives us the following values:

  • Model
  • Group
  • Language
  • Image Path
  • Author’s URL
  • Author’s Name
  • A list of sample queries
  • Skill Name
  • Licence and terms of use
  • Rating
  • Description

Implementation in SUSI iOS

The UI for listing skills is a little complex as it consists of a UITableView where each UITableViewCell consists of a UILabel(group name) and a UICollectionVIew (horizontal scroll).

Let’s see the step by step process to implement the skill listing.

  1. First, we need to fetch all the groups available using the endpoint above.
// get all groups
func getAllGroups() {
  Client.sharedInstance.getAllGroups { (groups, success, message) in
    DispatchQueue.main.async {
      if success {
        self.groups = groups
        self.tableView.reloadData()
      } else {
        print(message ?? "error")
      }
    }
  }
}
  1. After the response from the above call is obtained, the groups object containing all the groups is returned to the controller which the group name to set the UILabel.
var groupName: String? {
  didSet {
    backgroundColor = Color.grey.lighten3
    groupNameLabel.text = groupName
  }
}
  1. After the label is set, each cell makes another API call to populate the collection view, since these calls are concurrent, the collection view populates as soon as the response is fetched.
  2. The response from the above API call is used to create an array of Skill Model objects which is used to parse the response and to effectively use the data to display.
if let skills = response[Client.SkillListing.skills] as? [String : AnyObject],
  let model = response[Client.SkillListing.model] as? String,
  let group = response[Client.SkillListing.group] as? String,
  let language = response[Client.SkillListing.language] as? String,
  skills.count > 0 {
    let skillData = Skill.getAllSkill(skills, model, group, language)
    completion(skillData, true, nil)
    return
}
static func getAllSkill(_ skills: [String : AnyObject], _ model: String, _ group: String, _ language: String) -> [Skill] {
  var skillData = [Skill]()
  for skill in skills {
    let newSkill = Skill(dictionary: skill.value as! [String : AnyObject])
    newSkill.imagePath = getImagePath(model, group, language, newSkill.imagePath)
    skillData.append(newSkill)
  }
  return skillData
}
  1. At last, the skill object for the collection view is used to populate it as below:
var skill: Skill? {
  didSet {
    if let skill = skill {
      if let url = URL(string: skill.imagePath) {
        imageView.kf.setImage(with: url)
      }
      exampleQueryLabel.text = "\(skill.examples.first?.debugDescription ?? "")"
      skillNameLabel.text = skill.skillName
      skillDescription.text = skill.skillDescription
    }
  }
}

Here, we make use of the didSet method to populate the collection view. We have used Kingfisher to display the images.

That’s all for the scope of this tutorial. We learned how to fetch the skill groups followed by fetching the skills and displaying the skill data using the skill model object.

Below is the final UI we see after implementation.

Resources

Settings Controller UI using Static Table View

Dynamic Table Views are used at places where there may be any kind of reusability of cells. This means that there would exist cells that would have the same UI elements but would differ in the content being displayed. Initially the Settings Controller was built using UICollectionViewController which is completely dynamic but later I realized that the cells will remain static every time so there is no use of dynamic cells to display the UI hence, I switched to static table view cells. Using Static Table View is very easy. In this blog, I will explain how the implementation of the same was achieved in SUSI iOS app.

Let’s start by dragging and dropping a UITableViewController into the storyboard file.

The initial configuration of the UITableView has content as Dynamic Prototypes but we need Static cells so we choose them and make the sections count to 5 to suit our need. Also, to make the UI better, we choose the style as Grouped.

Now for each section, we have the control of statically adding UI elements so, we add all the settings with their corresponding section headers and obtain the following UI.

       

After creating this UI, we can refer any UI element independently be it in any of the cells. So here we create references to each of the UISlider and UISwitch so that we can trigger an action whenever the value of anyone of them changes to get their present state.

To create an action, simply create a function and add `@IBAction` in front so that they can be linked with the UI elements in the storyboard and then click and drag the circle next to the function to UI element it needs to be added. After successful linking, hovering over the same circle would reveal all the UI elements which trigger that function. Below is a method with the @IBAction identifier indicating it can be linked with the UI elements in the storyboard. This method is executed whenever any slider or switch value changes, which then updates the UserDefaults value as well sends an API request to update the setting for the user on the server.

@IBAction func settingChanged(sender: AnyObject?) {
        var params = [String: AnyObject]()
        var key: String = ""

        if let senderTag = sender?.tag {
            if senderTag == 0 {
                key = ControllerConstants.UserDefaultsKeys.enterToSend
            } else if senderTag == 1 {
                key = ControllerConstants.UserDefaultsKeys.micInput
            } else if senderTag == 2 {
                key = ControllerConstants.UserDefaultsKeys.hotwordEnabled
            } else if senderTag == 3 {
                key = ControllerConstants.UserDefaultsKeys.speechOutput
            } else if senderTag == 4 {
                key = ControllerConstants.UserDefaultsKeys.speechOutputAlwaysOn
            } else if senderTag == 5 {
                key = ControllerConstants.UserDefaultsKeys.speechRate
            } else if senderTag == 6 {
                key = ControllerConstants.UserDefaultsKeys.speechPitch
            }

            if let slider = sender as? UISlider {
                UserDefaults.standard.set(slider.value, forKey: key)
            } else {
                UserDefaults.standard.set(!UserDefaults.standard.bool(forKey: key), forKey: key)
            }

            params[ControllerConstants.key] = key as AnyObject
            params[ControllerConstants.value] = UserDefaults.standard.bool(forKey: key) as AnyObject

            if let delegate = UIApplication.shared.delegate as? AppDelegate, let user = delegate.currentUser {
                params[Client.UserKeys.AccessToken] = user.accessToken as AnyObject
                params[ControllerConstants.count] = 1 as AnyObject

                Client.sharedInstance.changeUserSettings(params) { (_, message) in
                    DispatchQueue.main.async {
                        self.view.makeToast(message)
                    }
                }
            }
        }
    }

References

Reset Password Functionality in SUSI iOS

Reset Password as the name suggests is one of the features in the SUSI iOS app which allows a user to change his/her password when they are logged in. This feature was added because a user would want to change his password sometimes to prevent unauthorized access or make his account security stronger. We can find many popular apps online such as Facebook, Gmail, which allow the user to reset their password. The way this is done is pretty simple and all we need from the user is his current and the new password he/she wants to set. In this blog post, I am going to explain step by step how this is implemented in the iOS client.

Implementation

The option to Reset Password is provided to the user under the Settings Controller. On selecting the row, the user is presented with another view which asks the user for his/her current password, new password, and another field to confirm the newly entered password.

First, the user needs to provide his current password followed by the new password. The user’s current password is required just to authenticate that the account’s owner is requesting the password change. The new password field is followed by another field called confirm password just to make sure there isn’t any typo.

Now when the field is filled, the user clicks the `Reset password` button at the bottom. What happens here is, first, the fields are validated to ensure the correct length of the passwords followed by an API request to update the same. The endpoint for the same is as below:

http://api.susi.ai/aaa/changepassword.json?changepassword=user_email&password=current _pass&newpassword=new_pass&access_token=user_access_token

This endpoint requires 3 things:

  • Current Password
  • New Password
  • User’s email
  • Access Token obtained at the time of login
func validatePassword() -> [Bool:String] {
        if let newPassword = newPasswordField.text,
            let confirmPassword = confirmPasswordField.text {
            if newPassword.characters.count > 5 {
                if newPassword == confirmPassword {
                    return [true: ""]
                } else {
                    return [false: ControllerConstants.passwordDoNotMatch]
                }
            } else {
                return [false: ControllerConstants.passwordLengthShort]
            }
        }
        return [false: Client.ResponseMessages.ServerError]
    }

Initially, we were not saving the user’s email, so we added the user’s email to the User’s object which is saved at the time of login.

if var userData = results {
userData[Client.UserKeys.EmailOfAccount] = user.email
UserDefaults.standard.set(userData, forKey: ControllerConstants.UserDefaultsKeys.user)
self.saveUserGlobally(user: currentUser)
}

At last, the API call is made which is implemented as below:

let params = [
  Client.UserKeys.AccessToken: user.accessToken,
  Client.UserKeys.EmailOfAccount: user.emailID,
  Client.UserKeys.Password: currentPasswordField.text ?? "",
  Client.UserKeys.NewPassword: newPasswordField.text ?? ""
]
Client.sharedInstance.resetPassword(params as [String : AnyObject], { (_, message) in
  DispatchQueue.main.async {
    self.view.makeToast(message)
    self.setUIActive(active: false)
  }
})

Below is the final UI.

Reference

How to Implement Feedback System in SUSI iOS

The SUSI iOS app provides responses for various queries but the response is always not accurate. To improve the response, we make use of the feedback system, which is the first step towards implementing Machine Learning on the SUSI Server. The way this works is that for every query, we present the user with an option to upvote or downvote the response and based on that a positive or negative feedback is saved on the server. In this blog, I will explain how this feedback system was implemented in the SUSI iOS app.

Steps to implement:

We start by adding the UI which is two buttons, one with a thumbs up and the other with a thumbs down image.

textBubbleView.addSubview(thumbUpIcon)
textBubbleView.addSubview(thumbDownIcon)
textBubbleView.addConstraintsWithFormat(format: "H:[v0]-4-[v1(14)]-2-[v2(14)]-8-|", views: timeLabel, thumbUpIcon, thumbDownIcon)
textBubbleView.addConstraintsWithFormat(format: "V:[v0(14)]-2-|", views: thumbUpIcon)
textBubbleView.addConstraintsWithFormat(format: "V:[v0(14)]-2-|", views: thumbDownIcon)
thumbUpIcon.isUserInteractionEnabled = true
thumbDownIcon.isUserInteractionEnabled = true

Here, we add the subviews and assign constraints so that these buttons align to the bottom right next to each other. Also, we enable the user interaction for these buttons.

We know that the user can rate the response by pressing either of the buttons added above. To do that we make an API call to the endpoint below:

BASE_URL+'/cms/rateSkill.json?'+'model='+model+'&group='+group+'&skill='+skill+’&language’+language+’&rating=’+rating

Here, the BASE_URL is the url of the server, the other three params model, group, language and skill are retrieved by parsing the skill location parameter we get with the response. The rating is positive or negative based on which button was pressed by the user. The skill param in the response looks like this:

skills:
[
"/susi_skill_data/models/general/entertainment/en/quotes.txt"
]

Let’s write the method that makes the API call and responds to the UI that it was successful.

if let accepted = response[ControllerConstants.accepted] as? Bool {
  if accepted {
    completion(true, nil)
    return
  }
  completion(false, ResponseMessages.ServerError)
  return
}

Here after receiving a response from the server, we check if the `accepted` variable is true or not. Based on that, we pass `true` or `false` to the completion handler. Below the response we actually receive by making the request.

{
session: {
identity: {
type: "host",
name: "23.105.140.146",
anonymous: true
}
},
accepted: true,
message: "Skill ratings updated"
}

Finally, let’s update the UI after the request has been successful.

if sender == thumbUpIcon {
thumbDownIcon.tintColor = UIColor(white: 0.1, alpha: 0.7)
thumbUpIcon.isUserInteractionEnabled = false
thumbDownIcon.isUserInteractionEnabled = true
feedback = "positive"
} else {
thumbUpIcon.tintColor = UIColor(white: 0.1, alpha: 0.7)
thumbDownIcon.isUserInteractionEnabled = false
thumbUpIcon.isUserInteractionEnabled = true
feedback = "negative"
}
sender.tintColor = UIColor.hexStringToUIColor(hex: "#2196F3")

Here, we check the sender (the thumbs up or down button) and based on that pass the rating (positive or negative) and update the color of the button.

Below is the app in action with the feedback system.

Resources:

Encoding and Decoding Images as Data in UserDefaults in SUSI iOS

In this blog post, I will be explaining how to encode and decode images and save them in UserDefaults so that the image persists even if it is removed from the Photos app. It happens a number of times that images are removed from the gallery by the users which results in the app loosing the image. So, to avoid this, we save the image by encoding it in a data object and save it inside UserDefaults. In SUSI iOS app we simply select an image from the image picker, encode it and save it in UserDefaults. To set the image, we simply fetch the image data from the UserDefaults and decode it to an image.

There are two ways we can do the encoding and decoding process:

  • Using Data object
  • Using Base64 string

For the scope of this tutorial, we will use the Data object.

Implementation Steps

  1. To use the image picker, we need to add permissions to `Info.plist` file.
<key>NSLocationWhenInUseUsageDescription</key>
<string>Susi is requesting to get your current location</string>
<key>NSPhotoLibraryUsageDescription</key>
<string>Susi needs to request your gallery access to select wallpaper</string>
  1. Select image from gallery

First, we present an alert which gives an option to select the image from the gallery.

// Show wallpaper options to set wallpaper or clear wallpaper
func showWallpaperOptions() {
  let imageDialog = UIAlertController(title: ControllerConstants.wallpaperOptionsTitle, message: nil, preferredStyle: UIAlertControllerStyle.alert)
  imageDialog.addAction(UIAlertAction(title: ControllerConstants.wallpaperOptionsPickAction, style: .default, handler: { (_: UIAlertAction!) in
  imageDialog.dismiss(animated: true, completion: nil)
  self.showImagePicker()
  }))
  imageDialog.addAction(UIAlertAction(title: ControllerConstants.wallpaperOptionsNoWallpaperAction, style: .default, handler: { (_: UIAlertAction!) in
    imageDialog.dismiss(animated: true, completion: nil)
    self.removeWallpaperFromUserDefaults()
  }))
  imageDialog.addAction(UIAlertAction(title: ControllerConstants.dialogCancelAction, style: .cancel, handler: { (_: UIAlertAction!) in
    imageDialog.dismiss(animated: true, completion: nil)
  }))
  self.present(imageDialog, animated: true, completion: nil)
}

Here, we create and UIAlertController with three options to select, one which presents the image picker controller, the second one removes the background wallpaper and the third dismisses the alert.

  1. Set the image as background view
// Callback when image is selected from gallery
func imagePickerController(_ picker: UIImagePickerController, didFinishPickingMediaWithInfo info: [String : Any]) {
  dismiss(animated: true, completion: nil)
  let chosenImage = info[UIImagePickerControllerOriginalImage] as? UIImage
  if let image = chosenImage {
    setBackgroundImage(image: image)
  }
}

We use the `didFinishPickingMediaWithInfo` delegate method to set the image as background. First we get the image using the the `info` dictionary using the `UIImagePickerControllerOriginalImage` key.

  1. Save the image in UserDefaults (encoding)
// Save image selected by user to user defaults
func saveWallpaperInUserDefaults(image: UIImage!) {
  let imageData = UIImageJPEGRepresentation(image!, 1.0)
  let defaults = UserDefaults.standard
  defaults.set(imageData, forKey: userDefaultsWallpaperKey)
}

We first convert the image to a data object using the `UIImageJPEGRepresentation` method followed by saving the data object in UserDefaults with the key `wallpaper`.

  1. Decode the data object back to UIImage 

Now whenever we need to decode the image, we simply get the data object from the UserDefaults and use it to display the image.

// Check if user defaults have an image data saved else return nil/Any
func getWallpaperFromUserDefaults() -> Any? {
  let defaults = UserDefaults.standard
  return defaults.object(forKey: userDefaultsWallpaperKey)
}

Below is the output when an image is selected and displayed as a background.

Resources:

Using The Dark and Light Theme in SUSI iOS

SUSI being an AI for interactive chat bots, provides answers to the users in the intelligent way. So, to make the SUSI iOS app more user friendly, the option of switching between themes was introduced. This also enables the user switch between themes based on the environment around. Any user can switch between the light and dark themes easily from the settings.

We start by declaring an enum called `theme` which contains two strings namely, dark and light.

enum theme: String {
    case light
    case dark
}

We can update the color scheme based on the theme selected very easily by checking the currently active theme and based on that check, we update the color scheme. To check the currently active theme, we define a variable in the `AppDelegate` which holds the value.

var activeTheme: String?

Below is the way the color scheme of the LoginViewController is set.

var activeTheme: String?func setupTheme() {
  let image = UIImage(named: ControllerConstants.susi)?.withRenderingMode(.alwaysTemplate)
  susiLogo.image = image
  susiLogo.tintColor = .white
  UIApplication.shared.statusBarStyle = .lightContent
  let activeTheme = AppDelegate().activeTheme
  if activeTheme == theme.light.rawValue {
    view.backgroundColor = UIColor.lightThemeBackground()
  } else if activeTheme == theme.dark.rawValue {
    view.backgroundColor = UIColor.darkThemeBackground()
  }
}

Here, we first get the image and set the rendering mode to `alwaysTemplate` so that we can change the tint color of the image. Next, we assign the image to the `IBOutlet` and change the tint color to `white`. We also change the status bar style to `lightContent`. Next, we check the active theme and change the view’s background color accordingly. For this method to execute, we call it inside, `viewDidLoad` so that the theme loads up as the view loads.

Next, lets add this option of switching between themes inside the `SettingsViewController`. We add a cell with `titleLabel` as `Change Theme` and use the collectionView’s delegate method of `didSelect` to show an alert. This alert contains three options, Dark theme, Light Theme and Cancel. Let’s code that method which presents the alert.

func themeToggleAlert() {
  let imageDialog = UIAlertController(title: ControllerConstants.toggleTheme, message: nil, preferredStyle: UIAlertControllerStyle.alert)
  imageDialog.addAction(UIAlertAction(title: theme.dark.rawValue.capitalized, style: .default, handler: { (_: UIAlertAction!) in
    imageDialog.dismiss(animated: true, completion: nil)
    AppDelegate().activeTheme = theme.dark.rawValue
    self.settingChanged(sender: self.imagePicker)
    self.setupTheme()
  }))
  imageDialog.addAction(UIAlertAction(title: theme.light.rawValue.capitalized, style: .default, handler: { (_: UIAlertAction!) in
    imageDialog.dismiss(animated: true, completion: nil)
    AppDelegate().activeTheme = theme.light.rawValue
    self.settingChanged(sender: self.imagePicker)
    self.setupTheme()
  }))
  imageDialog.addAction(UIAlertAction(title: ControllerConstants.dialogCancelAction, style: .cancel, handler: { (_: UIAlertAction!) in
    imageDialog.dismiss(animated: true, completion: nil)
  }))
  self.present(imageDialog, animated: true, completion: nil)
}

Here, we assign the alert view’s title and add 3 actions and their respective completion handlers. If we see inside these completion handlers, we can notice that we first dismiss the alert followed by updating the activeTheme variable in AppDelegate and call the `settingChanged` function which updates the user’s settings on the server. Finally, we update the color scheme.

Now, if we build and run the app and change the theme from the settings, we will notice that on returning to the chat view, the color scheme is not updated. The reason here is that we are setting up the theme on viewDidLoad which loads only once and is not executed until the controller is presented again. Here, we make use of the `viewDidAppear` method which executes every time the view appears.

override func viewDidAppear(_ animated: Bool) {
  super.viewDidAppear(animated)
  setupTheme()
}

To persist the selected theme, we used the UserDefaults to save the theme which got assigned everytime to the `activeTheme` variable when the app loads up.

UserDefaults.standard.set(AppDelegate().activeTheme, forKey: ControllerConstants.UserDefaultsKeys.theme)

On app launch, we assigned this User Default the value of the light theme as a default.

Below is the final output:

References:

How to Store and Retrieve User Settings from SUSI Server in SUSI iOS

Any user using the SUSI iOS client can set preferences like enabling or disabling the hot word recognition or enabling input from the microphone. These settings need to be stored, in order to be used across all platforms such as web, Android or iOS. Now, in order to store these settings and maintain a synchronization between all the clients, we make use of the SUSI server. The server provides an endpoint to retrieve these settings when the user logs in.

First, we will focus on storing settings on the server followed by retrieving settings from the server. The endpoint to store settings is as follows:

http://api.susi.ai/aaa/changeUserSettings.json?key=key&value=value&access_token=ACCESS_TOKEN

This takes the key value pair for storing a settings and an access token to identify the user as parameters in the GET request. Let’s start by creating the method that takes input the params, calls the API to store settings and returns a status specifying if the executed successfully or not.

 let url = getApiUrl(UserDefaults.standard.object(forKey: ControllerConstants.UserDefaultsKeys.ipAddress) as! String, Methods.UserSettings)

        _ = makeRequest(url, .get, [:], parameters: params, completion: { (results, message) in
            if let _ = message {
                completion(false, ResponseMessages.ServerError)
            } else if let results = results {
                guard let response = results as? [String : AnyObject] else {
                    completion(false, ResponseMessages.ServerError)
                    return
                }
                if let accepted = response[ControllerConstants.accepted] as? Bool, let message = response[Client.UserKeys.Message] as? String {
                    if accepted {
                        completion(true, message)
                        return
                    }
                    completion(false, message)
                    return
                }
            }
        })

Let’s understand this function line by line. First we generate the URL by supplying the server address and the method. Then, we pass the URL and the params in the `makeRequest` method which has a completion handler returning a results object and an error object. Inside the completion handler, check for any error, if it exists mark the request completed with an error else check for the results object to be a dictionary and a key `accepted`, if this key is `true` our request executed successfully and we mark the request to be executed successfully and finally return the method. After making this method, it needs to be called in the view controller, we do so by the following code.

Client.sharedInstance.changeUserSettings(params) { (_, message) in
  DispatchQueue.global().async {
    self.view.makeToast(message)
  }
}

The code above takes input params containing the user token and key-value pair for the setting that needs to be stored. This request runs on a background thread and displays a toast message with the result of the request.

Now that the settings have been stored on the server, we need to retrieve these settings every time the user logs in the app. Below is the endpoint for the same:

http://api.susi.ai/aaa/listUserSettings.json?access_token=ACCESS_TOKEN

This endpoint accepts the user token which is generated when the user logs in which is used to uniquely identify the user and his/her settings are returned. Let’s create the method that would call this endpoint and parse and save the settings data in the iOS app’s User Defaults.

if let _ = message {
  completion(false, ResponseMessages.ServerError)
} else if let results = results {
  guard let response = results as? [String : AnyObject] else {
    completion(false, ResponseMessages.ServerError)
    return
  }
  guard let settings = 
response[ControllerConstants.Settings.settings.lowercased()] as? [String:String] else {
    completion(false, ResponseMessages.ServerError)
    return
  }
  for (key, value) in settings {
    if value.toBool() != nil {
      UserDefaults.standard.set(value.toBool()!, forKey: key)
    } else {
      UserDefaults.standard.set(value, forKey: key)
    }
  }
  completion(true, response[Client.UserKeys.Message] as? String ?? "error")
}

Here, the creation of the URL is same as we created above the only difference being the method passed. We parse the settings key value into a dictionary followed by a loop which loop’s through all the keys and stores the value in the User Defaults for that key. We simply call this method just after user log in as follows:

Client.sharedInstance.fetchUserSettings(params as [String : AnyObject]) { (success, message) in
  DispatchQueue.global().async {
    print("User settings fetch status: \(success) : \(message)")
  }
}

That’s all for this tutorial where we learned how to store and retrieve settings on the SUSI Server.

References

Save Chat Messages using Realm in SUSI iOS

Fetching data from the server each time causes a network load which makes the app depend on the server and the network in order to display data. We use an offline database to store chat messages so that we can show messages to the user even if network is not present which makes the user experience better. Realm is used as a data storage solution due to its ease of usability and also, since it’s faster and more efficient to use. So in order to save messages received from the server locally in a database in SUSI iOS, we are using Realm and the reasons for using the same are mentioned below.

The major upsides of Realm are:

  • It’s absolutely free of charge,
  • Fast, and easy to use.
  • Unlimited use.
  • Work on its own persistence engine for speed and performance

Below are the steps to install and use Realm in the iOS Client:

Installation:

  • Install Cocoapods
  • Run `pod repo update` in the root folder
  • In your Podfile, add use_frameworks! and pod ‘RealmSwift’ to your main and test targets.
  • From the command line run `pod install`
  • Use the `.xcworkspace` file generated by Cocoapods in the project folder alongside `.xcodeproj` file

After installation we start by importing `Realm` in the `AppDelegate` file and start configuring Realm as below:

func initializeRealm() {
        var config = Realm.Configuration(schemaVersion: 1,
            migrationBlock: { _, oldSchemaVersion in
                if (oldSchemaVersion < 0) {
                    // Nothing to do!
                }
        })
        config.fileURL = config.fileURL?.deletingLastPathComponent().appendingPathComponent("susi.realm")
        Realm.Configuration.defaultConfiguration = config
}

Next, let’s head over to creating a few models which will be used to save the data to the DB as well as help retrieving that data so that it can be easily used. Since Susi server has a number of action types, we will cover some of the action types, their model and how they are used to store and retrieve data. Below are the currently available data types, that the server supports.

enum ActionType: String {
  case answer
  case websearch
  case rss
  case table
  case map 
  case anchor
}

Let’s start with the creation of the base model called `Message`. To make it a RealmObject, we import `RealmSwift` and inherit from `Object`

class Message: Object {
  dynamic var queryDate = NSDate()
  dynamic var answerDate = NSDate()
  dynamic var message: String = ""
  dynamic var fromUser = true
  dynamic var actionType = ActionType.answer.rawValue
  dynamic var answerData: AnswerAction?
  dynamic var mapData: MapAction?
  dynamic var anchorData: AnchorAction?
}

Let’s study these properties of the message one by one.

  • `queryDate`: saves the date-time the query was made
  • `answerDate`: saves the date-time the query response was received
  • `message`: stores the query/message that was sent to the server
  • `fromUser`: a boolean which keeps track who created the message
  • `actionType`: stores the action type
  • `answerData`, `rssData`, `mapData`, `anchorData` are the data objects that actually store the respective action’s data

To initialize this object, we need to create a method that takes input the data received from the server.

// saves query and answer date
if let queryDate = data[Client.ChatKeys.QueryDate] as? String,
let answerDate = data[Client.ChatKeys.AnswerDate] as? String {
  message.queryDate = dateFormatter.date(from: queryDate)! as NSDate
  message.answerDate = dateFormatter.date(from: answerDate)! as NSDate}if let type = action[Client.ChatKeys.ResponseType] as? String,
  let data = answers[0][Client.ChatKeys.Data] as? [[String : AnyObject]] {
  if type == ActionType.answer.rawValue {
     message.message = action[Client.ChatKeys.Expression] as! String
     message.actionType = ActionType.answer.rawValue
    message.answerData = AnswerAction(action: action)
  } else if type == ActionType.map.rawValue {
    message.actionType = ActionType.map.rawValue
    message.mapData = MapAction(action: action)
  } else if type == ActionType.anchor.rawValue {
    message.actionType = ActionType.anchor.rawValue
    message.anchorData = AnchorAction(action: action)
    message.message = message.anchorData!.text
  }
}

Since, the response from the server for a particular query might contain numerous action types, we create loop inside a method to capture all those action types and save each one of them. Since, there are multiple action types thus we need a list containing all the messages created for the action types. For each action in the loop, corresponding data is saved into their specific objects.

Let’s discuss the individual action objects now.

  • AnswerAction
class AnswerAction: Object {
  dynamic var expression: String = ""
  convenience init(action: [String : AnyObject]) {
    self.init()
    if let expression = action[Client.ChatKeys.Expression] as? String {
      self.expression = expression
    }
  }
}

 This is the simplest action type implementation. It contains a single property `expression` which is a string type. For initializing it, we take the action object and extract the expression key-value and save it.

if type == ActionType.answer.rawValue {
  message.message = action[Client.ChatKeys.Expression] as! String
  message.actionType = ActionType.answer.rawValue
  // pass action object and save data in `answerData`
  message.answerData = AnswerAction(action: action)
}

Above is the way an answer action is checked and data saved inside the `answerData` variable.

2)   MapAction

class MapAction: Object {
  dynamic var latitude: Double = 0.0
  dynamic var longitude: Double = 0.0
  dynamic var zoom: Int = 13

  convenience init(action: [String : AnyObject]) {
    self.init()
    if let latitude = action[Client.ChatKeys.Latitude] as? String,
    let longitude = action[Client.ChatKeys.Longitude] as? String,
    let zoom = action[Client.ChatKeys.Zoom] as? String {
      self.longitude = Double(longitude)!
      self.latitude = Double(latitude)!
      self.zoom = Int(zoom)!
    }
  }
}

This action implementation contains three properties, `latitude` `longitude` `zoom`. Since the server responds the values inside a string, each of them need to be converted to their respective type using force-casting. Default values are provided for each property in case some illegal value comes from the server.

3)   AnchorAction

class AnchorAction: Object {
  dynamic var link: String = ""
  dynamic var text: String = ""

  convenience init(action: [String : AnyObject]) {
    self.init()if let link = action[Client.ChatKeys.Link] as? String,
    let text = action[Client.ChatKeys.Text] as? String {
      self.link = link
      self.text = text
    }
  }
}

Here, the link to the openstreetmap website is saved in order to retrieve the image for displaying.

Finally, we need to call the API and create the message object and use the `write` clock of a realm instance to save it into the DB.

if success {
  self.collectionView?.performBatchUpdates({
    for message in messages! {
    // real write block
      try! self.realm.write {
        self.realm.add(message)
        self.messages.append(message)
        let indexPath = IndexPath(item: self.messages.count - 1, section: 0)
        self.collectionView?.insertItems(at: [indexPath])
      }
   }
}, completion: { (_) in
    self.scrollToLast()
  })
}

list of message items and inserted into the collection view.Below is the output of the Realm Browser which is a UI for viewing the database.

References:

Custom UI Implementation for Web Search and RSS actions in SUSI iOS Using Kingfisher for Image Caching

The SUSI Server is an AI powered server which is capable of responding to intelligent answers based on user’s queries. The queries to the susi server are obtained either as a websearch using the application or as an RSS feed. Two of the actions are websearch and RSS. These actions as the name suggests respond to queries based on search results from the web which are rendered in the clients. In order to use use these action types and display them in the SUSI iOS client, we need to first parse the actions looking for these action types and then creating a custom UI for them to display them.

To start with, we need to make send the query to the server to receive an intelligent response from the server. This response is parsed into different action types supported by the server and saved into relevant objects. Here, we check the action types by looping through the answers array containing the actions and based on that, we save the data for that action.

if type == ActionType.rss.rawValue {
   message.actionType = ActionType.rss.rawValue
   message.rssData = RSSAction(data: data, actionObject: action)
} else if type == ActionType.websearch.rawValue {
   message.actionType = ActionType.websearch.rawValue
   message.message = action[Client.ChatKeys.Query] as? String ?? ""
}

Here, we parsed the data response from the server and looked for the rss and websearch action type followed by which we saved the data we received from the server for each of the action types in their own objects.

Next, when a message object is created, we insert it into the dataSource item by appending it and use the `insertItems(at: [IndexPath])` method of collection view to insert them into the views at a particular index. Before adding them, we need to create a Custom UI for them. This UI will consist of a Collection View which is scrollable in the horizontal direction inside a CollectionView Cell. To start with this, we create a new class called `WebsearchCollectionView` which will be a `UIView` consisting of a `UICollectionView`.

We start by adding a collection view into the UIView inside the `init` method by overriding it. Declare a collection view using flow layout and scroll direction set to `horizontal`. Also, hide the scroll indicators and assign the delegate and datasource to `self`.

Now to populate this collection view, we need to specify the number of items that will show up. For this, we make use of the `message` variable declared. We use the `websearchData` in case of websearch action and `rssData` otherwise.

Now to specify the number of cells, we use the below method which returns the number of rss or websearch action objects and defaults to 0 such cells.

func collectionView(_ collectionView: UICollectionView, numberOfItemsInSection section: Int) -> Int {
    if let rssData = message?.rssData {
        return rssData.count
    } else if let webData = message?.websearchData {
        return webData.count
    }
    return 0
}

We display the title, description and image for each object for which we need to create a UI for the cells. Let’s start by creating a Custom Collection View cell with the imageview and 2 labels for title and description.

The imageview is given a contentMode of `aspectFit` and assigned a placeholder image in case the image doesn’t exist. The title and description labels are assigned the same font size, the title being bolder and both are center aligned.

class WebsearchCell: BaseCell {

   var imageView: UIImageView = {
       let iv = UIImageView()
       iv.contentMode = .scaleAspectFit
       iv.image = UIImage(named: "placeholder")
       return iv
   }()

   let titleLabel: UILabel = {
       let label = UILabel()
       label.textColor = .black
       label.font = UIFont.boldSystemFont(ofSize: 14)
       label.textAlignment = .center
       label.numberOfLines = 2
       label.backgroundColor = Color.grey.lighten3
       return label
   }()

   let descriptionLabel: UILabel = {
       let label = UILabel()
       label.font = UIFont.systemFont(ofSize: 14)
       label.textAlignment = .center
       return label
   }()

}

Next, we add constraints for each such view adding a title and description label adding a small margin on both sides of the cell for a cleaner UI.

addSubview(imageView)
addSubview(titleLabel)
addSubview(descriptionLabel)
descriptionLabel.numberOfLines = 5
addConstraintsWithFormat(format: "H:|-4-[v0(\(frame.width * 0.4))]-4-[v1]-4-|", views: imageView, titleLabel)
addConstraintsWithFormat(format: "|-\(frame.width * 0.4 + 8)-[v0]-4-|", views: descriptionLabel)
addConstraintsWithFormat(format: "V:|-4-[v0]-4-|", views: imageView)
addConstraintsWithFormat(format: "V:|-4-[v0(44)]-4-[v1]-4-|", views: titleLabel, descriptionLabel)

Now to use this custom cell, we first need to register it with the collection view and then we can use it easily in the `cellForItemAt` method. Since we are using Kingfisher for image caching, we use the `.kf.setImage` method to download the image from a URL and cache it as soon as it is downloaded.

collectionView.register(WebsearchCell.self, forCellWithReuseIdentifier: cellId)
 func collectionView(_ collectionView: UICollectionView, cellForItemAt indexPath: IndexPath) -> UICollectionViewCell {
       if let cell = collectionView.dequeueReusableCell(withReuseIdentifier: cellId, for: indexPath) as? WebsearchCell {
           cell.backgroundColor = .white

           if message?.actionType == ActionType.rss.rawValue {
               let feed = message?.rssData?.rssFeed[indexPath.item]
               cell.titleLabel.text = feed?.title
               cell.descriptionLabel.text = feed?.desc                cell.imageView.kf.setImage(with: URL(string: feed?.rssData?.image))
           } else if message?.actionType == ActionType.websearch.rawValue {
               let webData = message?.websearchData[indexPath.item]
               cell.titleLabel.text = webData?.title
               cell.descriptionLabel.text = webData?.desc.html2String                cell.imageView.kf.setImage(with: URL(string: feed?.webData?.image))
           }
           return cell
       } else {
           return UICollectionViewCell()
       }
   }

We check the action type and assign data based on that. Also, for the images, if they don’t exist a placeholder is added.

Since we are done with the Custom UI of the cell, we need to add it to the chat cell. For that, we add this `UIView` as a subview. For reasons of reusability, the cell was extracted into a separate one and call the `prepareForReuse()` method for reusability. This is followed by adding a subview and setting constraints for each cell and assigning the message object.

class RSSCell: ChatMessageCell {

   var message: Message? {
       didSet {
           self.addWebsearchView()
       }
   }

   lazy var websearchView: WebsearchCollectionView = {
       let view = WebsearchCollectionView()
       return view
   }()

   override func setupViews() {
       super.setupViews()
       prepareForReuse()
   }

   func addWebsearchView() {
       self.addSubview(websearchView)
       self.addConstraintsWithFormat(format: "H:|[v0]|", views: websearchView)
       self.addConstraintsWithFormat(format: "V:[v0(135)]", views: websearchView)
       websearchView.message = message
   }

}
if message.actionType == ActionType.rss.rawValue || message.actionType == ActionType.websearch.rawValue {
   if let cell = collectionView.dequeueReusableCell(withReuseIdentifier: ControllerConstants.rssCell, for: indexPath) as? RSSCell {
       cell.message = message
       return cell
   } else {
       return UICollectionViewCell()
   }
}

This is all we need to add a custom UI to a chat cell in SUSI iOS, very simple and clean.

Check the screenshot below, the app in action.

Resources:

Hotword Recognition in SUSI iOS

Hot word recognition is a feature by which a specific action can be performed each time a specific word is spoken. There is a service called Snowboy which helps us achieve this for various clients (for ex: iOS, Android, Raspberry pi, etc.). It is basically a DNN based hotword recognition toolkit.

In this blog, we will learn how to integrate the snowboy hotword detection wrapper in the SUSI iOS client. This service can be used in any open source project but for using it commercially, a commercial license needs to be obtained.

Following are the files that need to be added to the project which are provided by the service itself: snowboy-detect.h libsnowboy-detect.a and a trained model file which can be created using their online service: snowboy.kitt.ai. For the sake of this blog, we will be using the hotword “Susi”, the model file can be found here.

The way how snowboy works is that speech is recorded for a few seconds and this data is detected with an already trained model by a specific hotword, now if snowboy returns a 1 means word has been successfully detected else wasn’t.

We start with creation of a wrapper class in Objective-C which can be found wrapper and the bridging header in case this needs to be added to a Swift project. The wrapper contains methods for setting sensitivity, audio gain and running the detection using the buffer. It is a wrapper class built on top of the snowboy-detect.h header file.

Let’s initialize the service and run it. Below are the steps followed to enable hotword recognition and print out whether it successfully detected the hotword or not:

  • Create a ViewController class with extensions
    • AVAudioRecorderDelegate
    • AVAudioPlayerDelegate

since we will be recording speech.

  • Import AVFoundation
  • Create a basic layout containing a label which detects whether hotword detected or not and create corresponding `IBOutlet` in the ViewController and a button to trigger the start and stop of recognition.
  • Create the following variables:
    • let WAKE_WORD = “Susi” // hotword used
    • let RESOURCE = Bundle.main.path(forResource: “common”, ofType: “res”)
    • let MODEL = Bundle.main.path(forResource: “susi”, ofType: “umdl”) //path where the model file is stored
    • var wrapper: SnowboyWrapper! = nil // wrapper instance for running detection
    • var audioRecorder: AVAudioRecorder! // audio recorder instance
    • var audioPlayer: AVAudioPlayer!
    • var soundFileURL: URL! //stores the URL of the temp reording file
    • var timer: Timer! //timer to fire a function after an interval
    • var isStarted = false // variable to check if audio recorder already started
  • In `viewDidLoad` initialize the wrapper and set sensitivity and audio gain. Recognition best happens when sensitivity is set to `0.5` and audio gain is set to `1.0` according to the docs.
override func viewDidLoad() {
    super.viewDidLoad()
    wrapper = SnowboyWrapper(resources: RESOURCE, modelStr: MODEL)
    wrapper.setSensitivity("0.5")
    wrapper.setAudioGain(1.0)
}
  • Create an `IBAction` for the button to start recognition. This action will be used to start or stop the recording in which the action toggles based on the `isStarted` variable. When true, recording is stopped and the timer invalidated else a timer is started which calls the `startRecording` method with an interval of 4 seconds.
@IBAction func onClickBtn(_ sender: Any) {
  if (isStarted) {
    stopRecording()
    timer.invalidate()
    btn.setTitle("Start", for: .normal)
    isStarted = false
  } else {
    timer = Timer.scheduledTimer(timeInterval: 4, target: self, 
    selector: #selector(startRecording), userInfo: nil, repeats: true)
    timer.fire()
    btn.setTitle("Stop", for: .normal)
    isStarted = true
  }
}
  • Next, we add the start and stop recording methods.
    • First, a temp file is created which stores the recorded audio output
    • After which, necessary record configurations are made such as setting the sampling rate.
    • The recording is then started and the output stored in the temp file.
func startRecording() {
  do {
    let fileMgr = FileManager.default
    let dirPaths = fileMgr.urls(for: .documentDirectory, in: .userDomainMask)
    soundFileURL = dirPaths[0].appendingPathComponent("temp.wav")
    let recordSettings = [AVEncoderAudioQualityKey: 
    AVAudioQuality.high.rawValue,
    AVEncoderBitRateKey: 128000,
    AVNumberOfChannelsKey: 1,
    AVSampleRateKey: 16000.0] as [String : Any]
    let audioSession = AVAudioSession.sharedInstance()
    try audioSession.setCategory(AVAudioSessionCategoryRecord)
    try audioRecorder = AVAudioRecorder(url: soundFileURL,
settings: recordSettings as [String : AnyObject])
    audioRecorder.delegate = self
    audioRecorder.prepareToRecord()
    audioRecorder.record(forDuration: 2.0)
    instructionLabel.text = "Speak wake word: \(WAKE_WORD)"print("Started recording...")
  } catch let error {
    print("Audio session error: \(error.localizedDescription)")
  }
}
  • The stop recording method, stops the audioRecorder instance and updates the instruction label to show the same.
func stopRecording() {
  if (audioRecorder != nil && audioRecorder.isRecording) {
    audioRecorder.stop()
  }
  instructionLabel.text = "Stop"
  print("Stopped recording...")
}

The final recognition is done in the `audioRecorderDidFinishRecording` delegate method which runs the snowboy detection function which processes the audio recording in the temp file by creating a buffer and storing the audio in it and giving the wrapper this buffer as input which processes the buffer and returning a `1` is hotword was successfully detected.

func runSnowboy() {
  let file = try! AVAudioFile(forReading: soundFileURL)
  let format = AVAudioFormat(commonFormat: .pcmFormatFloat32, 
  sampleRate: 16000.0, channels: 1, interleaved: false)
  let buffer = AVAudioPCMBuffer(pcmFormat: format, frameCapacity: AVAudioFrameCount(file.length))
  try! file.read(into: buffer)
  let array = Array(UnsafeBufferPointer(start: 
  buffer.floatChannelData![0], count:Int(buffer.frameLength)))
  // print output
  let result = wrapper.runDetection(array, length: Int32(buffer.frameLength))
  print("Result: \(result)")
}

To test this out, click the start button and speak different words and you will notice that once the Hot Word is spoken, log with `result: 1` is printed out.

The snowboy hotword recognition also offers to train the personalized model with the help of Rest Apis for which the docs can be found here. The complete project implementation can be found here.

Sources: