Android library

Documentation for the Flowstorm Android library
The Flowstorm Android library was created to allow easy creation of voice-enabled applications or adding support for the Flowstorm communication into custom applications. This page describes how to import and use the library.


First, you need to define the repositories for the dependencies. Put the definition in your project's settings.gradle file:
repositories {
maven { url = uri("") }
maven { url = uri("") }
maven { url = uri("") }
maven { url = uri("") }
The library is imported by inserting the following code into your app's build.gradle.kts file:
isTransitive = true
exclude("org.jetbrains.kotlin", "kotlin-compiler-embeddable")
exclude("org.apache.tika", "tika-core")
exclude("javax.activation", "activation")
exclude("", "")
exclude("jakarta.xml.bind", "jakarta.xml.bind-api")
Or if you use the build.gradle file with the Java syntax:
implementation("ai.flowstorm.client.shared:flowstorm-client-shared-android:1.0.0-SNAPSHOT") {
exclude group: "org.jetbrains.kotlin", module: "kotlin-compiler-embeddable"
exclude group: "org.apache.tika", module: "tika-core"
exclude group: "javax.activation", module: "activation"
exclude group: "", module: ""
exclude group: "jakarta.xml.bind", module: "jakarta.xml.bind-api"
The attribute isTransitive is required because the library is distributed in the AAR format which does not include the dependencies the library requires. The excludes serve to avoid "duplicate classes" error.
If you encounter the error
Duplicate class androidx.lifecycle.ViewModelLazy found in modules lifecycle-viewmodel-2.5.0-runtime (androidx.lifecycle:lifecycle-viewmodel:2.5.0) and lifecycle-viewmodel-ktx-2.4.0-alpha03-runtime (androidx.lifecycle:lifecycle-viewmodel-ktx:2.4.0-alpha03)
Duplicate class androidx.lifecycle.ViewTreeViewModelKt found in modules lifecycle-viewmodel-2.5.0-runtime (androidx.lifecycle:lifecycle-viewmodel:2.5.0) and lifecycle-viewmodel-ktx-2.4.0-alpha03-runtime (androidx.lifecycle:lifecycle-viewmodel-ktx:2.4.0-alpha03)
try adding these dependencies:
implementation "androidx.lifecycle:lifecycle-viewmodel:2.5.0"
implementation "androidx.lifecycle:lifecycle-viewmodel-ktx:2.5.0"

Speech recognition

If you use the speech recognition function, you will need to obtain the user's permission to use the microphone. However, the library already includes the permission definition in its AndroidManifest file and it asks the user at an appropriate time, before the ASR is needed.
Also, if the user has the "Google" application disabled on their phone, the ASR won't work.

Importing the library

Create an Application file in your root package and make it extend the MainApplication class.
class Application : MainApplication() {
override fun onCreate() {
The initializeApp() function must be called before the super.onCreate() function. If you switch them, the app could overwrite your custom preferences (described in the Configuring the client section).
Next, create an entry activity:
class MainActivity : AppCompatActivity() {
Define the application and the activity it in the AndroidManifest.xml file with
<action android:name="android.intent.action.MAIN" />
<category android:name="android.intent.category.LAUNCHER" />

Running an activity from the library

This example shows how to start a conversation activity in chat mode, with default settings. For more info about available activities, see the Library contents section. In your activity, simply add
fun runChatActivity() {
val intent = Intent(this,
overridePendingTransition(android.R.anim.fade_in, android.R.anim.fade_out)
Upon reaching this block of code, the conversation with Flowstorm will start. You can, for example, add it to your onCreate function:
class MainActivity : AppCompatActivity() {
override fun onCreate() {
fun runChatActivity() {
val intent = Intent(this,
overridePendingTransition(android.R.anim.fade_in, android.R.anim.fade_out)

Configuring the client

The initializeApp() function takes an argument customDefaults of type FlowstormDefaults. By creating your class which extends that one, you can configure the client for your needs. This is the structure of the class, along with the default parameters:
open class FlowstormDefaults: Defaults {
override val appKey = "624c00370cf9df6d5508c088"
override val language = "en_US"
override val coreHost = ""
override val personaListUrl: String = ""
override val name = "flowstorm"
override val preferredInteractionModel: String =
override val autoStart = true
override val clientVersion: String = "2"
override val sentryForceLogging: Boolean = false
override val debugMode: Boolean = false
override val enableAvatar: Boolean = false
override val streamHost = ""
override val iceServerUri = ""
  • appKey (String) - The key to your conversational application. It can be obtained in the Flowstorm Studio
  • language (String) - The language which will be used in the speech recognition
  • coreHost (String) - The URL of the Flowstorm backend
  • personaListUrl (String) - The URL for your persona configuration. For the application to display a picture and a name of a persona it needs this configuration file where the mapping from voice to persona is defined. If you use custom voices, you can download the file from the default URL, extend it with your own personas, upload it elsewhere and link it here.
  • name (String) - this will be used in the clientType field during communication
  • preferredInteractionModel (PreferredInteractionModel) - If the conversation is launched through MenuActivity, but the dialogue does not start with the #modules command, this will be the interaction mode used.
  • autoStart (Boolean) - sets whether to start the conversation automatically by sending #intro input
  • clientVersion (String) - whether to communicate using socket (1) or using HTTP (2)
  • sentryForceLogging (Boolean) - if true, the Sentry module (if enabled) will log all events. If false, only 10% of events will be logged. More about Sentry in the Logging section.
  • debugMode (Boolean) - Enables certain UI elements
  • enableAvatar (Boolean) - If true, starts the application with the 3D avatar stream enabled
  • streamHost (String) - The URL of the avatar stream
  • iceServerUri (String) - The URL of the STUN server
The most important/useful parameters are probably appKey, language and name.

Library contents

The main features of the library are the two conversational and three other activities/screens. The activities are self-sufficient, the library contains everything to make them work - dependency definitions, user permission requests, layouts (and other resources), and imported classes.
Menu activity
Voice activity
Chat activity

Voice activity

The first conversation screen, voice activity implements the "voice mode". The layout is designed to resemble a phone call. The red button ends the conversation. The speaker button turns off and on audio output. The bubble button turns on and off subtitles, both for the persona and for the user. The microphone icon will flash green when the user is supposed to speak, the persona image will flash white when the persona speaks.

Chat activity

The other conversation screen chat activity implements the "chat mode". The layout is designed to resemble an instant messaging application. The messages from the persona will appear on the left. The user can type their message using the input field, then send them.
A screen that displays a selection of personas. Swiping the upper part changes between personas while swiping the lower part changes between topics the persona knows (if there is more than one). Clicking the phone receiver starts the voice mode, clicking the speech bubble starts the chat mode. The user can also make the persona introduce themselves by clicking the video. The buttons in the upper part of the screen lead to settings (left) and profile (right).

Profile activity and settings activity

The profile activity is a screen where the info about the user is displayed, in the settings, the user can configure the app.

Speech recognition

Each class of the library can of course be imported on its own. To name one example, the importing application can use the Android ASR in the class FlowstormSpeechRecognizer. To initialize it, you need to pass a RecognitionListener - for that, you can use the FlowstormRecognitionListener, or extend it. After that, call the createSpeechRecognizer() function. The function returns a boolean value which indicates whether the creation was successful. Afterwards, call startListening() to begin the ASR. You can also interrupt it by calling stopListening().


You can also make use only of the communication component, which is located in the Service class. To instantiate it, you need a pass a UI callback object and a configuration object. You can use the Callback class provided but for that, you will need a class that will implement the ClientUI interface and will display the content received from the server on the screen. Alternatively, you can provide your class implementing ClientCallbackV1. This is how you create the service:
val context = // android.content.Context
val clientUI = MyClientUI() // class implementing ClientUI interface
val zoneId = // ai.flowstorm.time.ZoneId
val localConfig = LocalConfig(zoneId = zoneId)
val service = Service(Callback(clientUI, context), localConfig)
Communication is started with
To send input from the user, add
val text: String = // obtain input from the user


The library supports two methods of logging: Firebase and Sentry.


To make the library use Firebase, you need to enable the Firebase support in your application. That is described here. Then, you need to pass a FirebaseAnalytics object to the initializeApp() function.
class MainApplication : Application() {
override fun onCreate() {
// ...
val firebaseAnalytics =
val appModule = FlowstormInitializer.initializeApp(this, analytics = firebaseAnalytics).apply { }
You also need to provide your google-services.json file.


To enable Sentry logging, add the following lines to the AndroidManifest.xml file under the <application> tag:
<meta-data android:name="io.sentry.dsn" android:value="YOUR_SENTRY_DSN_KEY" />
<meta-data android:name="io.sentry.traces.sample-rate" android:value="1.0" />
<meta-data android:name="io.sentry.sample-rate" android:value="1.0" />


The library contains support for receiving Firebase notifications. First, add the dependency to your project-level build.gradle file:
dependencies {
// Other dependencies...
Then, add a plugin to your module-level build.gradle file:
plugins {
// Other plugins...
Lastly, add this snippet to your AndroidManifest.xml file:
<action android:name="" />
Similarly to the Firebase logging, you will need a google-services.json file.


The library allows changing strings, themes, colors, images and even layouts. Any resource can be overwritten by a file or element of the same name in your application. For example, to change the default loading animation, you need to provide a drawable file named loading_spin_anim.xml. You can check the original names in the library files.


The default theme for the library is called Theme.Flowstorm. You can inherit from it and change certain colors.
<style name="Theme.Custom" parent="Theme.Flowstorm">
<item name="colorPrimary">@color/white</item>
Then, you need to replace the theme in your AndroidManifest.xml file:


<color name="sand_basic">#FF018786</color>


<string name="settings_language">Speech recognition language</string>


In theory, you can change even the layouts of the activities, if you provide a file named e.g. voice_activity.xml. However, your layout would need to contain elements with all ids which are present in the library layout, or else the application would crash after trying to access UI elements whose elements would be missing.

Custom settings options

Koin modules

The library uses the Koin library for module injection. Add the dependency to your build.gradle.kts file using

Custom preferences

You can override the Preferences object to add your config options:
class CustomPreferences(application: Application) : Preferences(application) {
They should be loaded into Koin as a module in your Application's onCreate function:
var appModule = module {
single { CustomPreferences(get()) }
If you have your own Koin modules, you can also add them using the loadKoinModules function. Also, you should load default values from your Preferences to the Android SharedPreferences:
val customPreferences: CustomPreferences = getKoin().get()