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‎content/install-guides/_images/connect-via-local-host.png‎

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‎content/install-guides/_images/performix-add-passwrd.png‎

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‎content/install-guides/flatpak.md‎

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author: "Jason Andrews"
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description: "Install Flatpak on Arm Linux, add the Flathub remote, and verify the setup by installing and running a native aarch64 application."
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weight: 1
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draft: true
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tool_install: true
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layout: installtoolsall
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multi_install: false

‎content/install-guides/performix.md‎

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sudo visudo
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```
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Add the following line, replacing `<username>` with your actual username:
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Add the following line, replacing `<username>` with your actual username. Insert it after any existing entries for that user or their groups, since rules in the sudoers file are applied in order and later entries take precedence.
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```bash
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<username> ALL=(ALL) NOPASSWD:ALL
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You can add multiple jump nodes. The order matters—your connection uses them in sequence. Use drag and drop to reorder jump nodes.
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#### Connect using the Arm Performix GUI to a local machine
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Performix already includes a built-in `localhost` target through the CLI. However, as of Performix 2026.01, this target is not exposed in the GUI. If you prefer the command line, you can run recipes directly without configuring the target through the GUI. [Skip to the profile the local machine section](#profile-the-local-machine) below.
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If you want to target your local machine conveniently through the GUI, use `localhost` in place of `target_host` and select **Username and password** as the authentication method, as shown in the following image. Make sure passwordless `sudo` is enabled for your user account.
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![Arm Performix GUI showing the Configure Target form for a local connection using 'localhost', including Host set to localhost, Name field for a custom label, Port set to 22, User set to the local username, authentication set to Username and password, and Host Key Verification options#center](/install-guides/_images/connect-via-local-host.png "Configure local target using localhost in Arm Performix GUI")
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Enter the password for your user when prompted
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![Arm Performix GUI displaying a password prompt dialog requesting the user's system password for authentication, including a password input field, confirmation button, and context indicating connection to a localhost target#center](/install-guides/_images/performix-add-passwrd.png "Enter user password for localhost authentication in Arm Performix")
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### Connect using the Arm Performix CLI
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The CLI is useful for Linux hosts or when you prefer command-line workflows.

‎content/learning-paths/mobile-graphics-and-gaming/android-ai-chat-lib/_index.md‎

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---
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title: Add an LLM to your Android app with Arm's AI Chat library
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draft: true
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cascade:
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draft: true
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minutes_to_complete: 15
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who_is_this_for: This is an introductory topic for developers who want to add a local, on-device LLM chat experience using Arm's AI Chat library, Kotlin, and Android Studio.
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learning_objectives:
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- Create a simple Android chatbot app scaffold in Android Studio
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- Load a mobile-friendly GGUF model on-device and run streamed chat inference
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prerequisites:
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- Android Studio
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- Android phone for testing (in Developer Mode, with USB cable to connect)
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author: Ben Clark
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### Tags
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skilllevels: Introductory
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subjects: ML
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armips:
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- Arm AI Chat library
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tools_software_languages:
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- Kotlin
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- Neon
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- SVE2
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- SME2
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- LLM
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operatingsystems:
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- Android
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further_reading:
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- resource:
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title: AI Chat - Explore and evaluate LLMs on Android and ChromeOS
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link: https://developer.arm.com/community/arm-community-blogs/b/announcements/posts/ai-chat-explore-and-evaluate-llms-on-android-and-chromeos
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type: blog
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- resource:
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title: Arm AI Chat LLM test app
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link: https://play.google.com/store/apps/details?id=com.arm.aichat
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type: example app
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- resource:
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title: AI Chat library @ Maven Central
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link: https://central.sonatype.com/artifact/com.arm/ai-chat
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type: documentation
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- resource:
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title: AI Chat library on GitHub
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link: https://github.com/arm/ai-chat
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type: website
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- resource:
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title: Arm KleidiAI - Helping AI frameworks elevate their performance on Arm CPUs
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link: https://developer.arm.com/community/arm-community-blogs/b/ai-blog/posts/kleidiai
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type: blog
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- resource:
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title: SME2
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link: https://www.arm.com/technologies/sme2
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type: website
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### FIXED, DO NOT MODIFY
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# ================================================================================
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weight: 1 # _index.md always has weight of 1 to order correctly
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layout: "learningpathall" # All files under learning paths have this same wrapper
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learning_path_main_page: "yes" # This should be surfaced when looking for related content. Only set for _index.md of learning path content.
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---

‎content/learning-paths/mobile-graphics-and-gaming/android-ai-chat-lib/_next-steps.md‎

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---
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# ================================================================================
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# FIXED, DO NOT MODIFY THIS FILE
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# ================================================================================
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weight: 21 # The weight controls the order of the pages. _index.md always has weight 1.
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title: "Next Steps" # Always the same, html page title.
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layout: "learningpathall" # All files under learning paths have this same wrapper for Hugo processing.
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---

‎content/learning-paths/mobile-graphics-and-gaming/android-ai-chat-lib/add-ai-chat-lib-2.md‎

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---
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title: Add AI Chat Library
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weight: 3
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### FIXED, DO NOT MODIFY
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layout: learningpathall
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---
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Your freshly created Android Studio project should already have top-level repositories including `google()` and `mavenCentral()` in `settings.gradle.kts`, but check that it does, to ensure the app can find the library.
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## Add the Maven Dependency
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We need to add the AI Chat library in the app module build file, `app/build.gradle.kts` (not the project `build.gradle.kts` in the root of the project).
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In here we add into the `dependencies` section at the bottom:
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```kotlin
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implementation("com.arm:ai-chat:0.1.0")
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```
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This adds the library to your project, and all the LLM functionality. Also in this file, check that:
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- `targetSdk` and `compileSdk` are 36
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- the Java version in `compileOptions` is `JavaVersion.VERSION_17`
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- the `jvmTarget` in `kotlinOptions` is 17
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In `libs.version.toml`, check that:
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- `kotlin` version is `2.2.20`
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Finally, there will be a banner at the top of these settings files saying the "Gradle files have changed since last project sync." Choose the option to "Sync Now", and let the project update.
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## Adjust the Manifest
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We need to adjust the `AndroidManifest.xml` file, which is in `app\src\main`.
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Most of the file is an xml tag `<application ...>`. Within the tag are several `android:` options. Add in an additional flag to load the needed llama.cpp native libraries:
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```xml
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<application
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...
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android:extractNativeLibs="true"
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... >
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```

‎content/learning-paths/mobile-graphics-and-gaming/android-ai-chat-lib/add-layouts-adapter-3.md‎

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---
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title: Add UI Code
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weight: 4
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### FIXED, DO NOT MODIFY
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layout: learningpathall
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---
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## Add Layouts
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Currently the `activity_main.xml` layout file in your `app\src\main\res\layout` directory is nearly empty, containing just a "Hello World!" piece of text that we wish to remove. Instead, replace it with the following, which will create a status area at the top, a place for messages in the middle, and a place for you to type at the bottom with a button to send:
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```xml
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<?xml version="1.0" encoding="utf-8"?>
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<androidx.constraintlayout.widget.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
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xmlns:app="http://schemas.android.com/apk/res-auto"
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android:id="@+id/root"
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android:layout_width="match_parent"
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android:layout_height="match_parent">
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<TextView
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android:id="@+id/status_text"
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android:layout_width="0dp"
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android:layout_height="wrap_content"
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android:layout_marginStart="16dp"
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android:layout_marginTop="16dp"
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android:layout_marginEnd="16dp"
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android:text="Loading model..."
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android:textAppearance="@style/TextAppearance.MaterialComponents.Body1"
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app:layout_constraintEnd_toEndOf="parent"
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app:layout_constraintStart_toStartOf="parent"
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app:layout_constraintTop_toTopOf="parent" />
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<androidx.recyclerview.widget.RecyclerView
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android:id="@+id/messages"
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android:layout_width="0dp"
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android:layout_height="0dp"
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android:layout_marginStart="16dp"
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android:layout_marginTop="12dp"
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android:layout_marginEnd="16dp"
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android:clipToPadding="false"
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android:paddingBottom="8dp"
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app:layout_constraintBottom_toTopOf="@+id/input_row"
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app:layout_constraintEnd_toEndOf="parent"
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app:layout_constraintStart_toStartOf="parent"
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app:layout_constraintTop_toBottomOf="@+id/status_text" />
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<LinearLayout
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android:id="@+id/input_row"
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android:layout_width="0dp"
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android:layout_height="wrap_content"
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android:layout_margin="16dp"
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android:orientation="horizontal"
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app:layout_constraintBottom_toBottomOf="parent"
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app:layout_constraintEnd_toEndOf="parent"
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app:layout_constraintStart_toStartOf="parent">
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<EditText
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android:id="@+id/user_input"
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android:layout_width="0dp"
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android:layout_height="wrap_content"
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android:layout_weight="1"
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android:enabled="false"
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android:hint="Model is loading..."
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android:inputType="textMultiLine"
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android:maxLines="4"
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android:minHeight="48dp"
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android:padding="12dp" />
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<com.google.android.material.button.MaterialButton
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android:id="@+id/send_button"
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android:layout_width="wrap_content"
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android:layout_height="wrap_content"
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android:layout_marginStart="12dp"
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android:enabled="false"
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android:text="Import model" />
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</LinearLayout>
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</androidx.constraintlayout.widget.ConstraintLayout>
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```
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We also need two small "helper" layouts to format the messages from the user and the AI assistant. In the `layout` folder alongside the main layout, first create `item_message_user.xml` and insert the following:
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```xml
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<?xml version="1.0" encoding="utf-8"?>
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<FrameLayout xmlns:android="http://schemas.android.com/apk/res/android"
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android:layout_width="match_parent"
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android:layout_height="wrap_content"
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android:paddingTop="6dp"
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android:paddingBottom="6dp">
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<TextView
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android:id="@+id/msg_content"
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android:layout_width="wrap_content"
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android:layout_height="wrap_content"
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android:layout_gravity="end"
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android:background="#D7F0FF"
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android:padding="12dp"
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android:textAppearance="@style/TextAppearance.MaterialComponents.Body1" />
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</FrameLayout>
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```
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Then create `item_message_assistant.xml` and put the following as its contents:
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```xml
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<?xml version="1.0" encoding="utf-8"?>
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<FrameLayout xmlns:android="http://schemas.android.com/apk/res/android"
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android:layout_width="match_parent"
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android:layout_height="wrap_content"
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android:paddingTop="6dp"
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android:paddingBottom="6dp">
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<TextView
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android:id="@+id/msg_content"
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android:layout_width="wrap_content"
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android:layout_height="wrap_content"
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android:layout_gravity="start"
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android:background="#EFEFEF"
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android:padding="12dp"
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android:textAppearance="@style/TextAppearance.MaterialComponents.Body1" />
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</FrameLayout>
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```
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## Add the MessageAdaptor class
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As a final bit of UI code, we add a `MessageAdapter.kt` code file to put our messages into the correct bit of layout. The file should sit alongside the `MainActivity` class that is auto-created with the project.
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{{% notice Package name %}}
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The `package` name below has to match that of your project name. If you named your project `simpleaichat`, you can copy the block without changes. If you named your project differently as you started out this Learning Path, make sure you update it after populating the file.
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{{% /notice %}}
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The file contents of `MessageAdapter.kt` are:
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```kotlin
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package com.example.simpleaichat
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import android.view.LayoutInflater
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import android.view.View
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import android.view.ViewGroup
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import android.widget.TextView
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import androidx.recyclerview.widget.RecyclerView
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data class Message(
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val id: String,
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val content: String,
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val isUser: Boolean
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)
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class MessageAdapter(
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private val messages: List<Message>
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) : RecyclerView.Adapter<RecyclerView.ViewHolder>() {
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override fun getItemViewType(position: Int): Int {
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return if (messages[position].isUser) VIEW_TYPE_USER else VIEW_TYPE_ASSISTANT
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}
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override fun onCreateViewHolder(parent: ViewGroup, viewType: Int): RecyclerView.ViewHolder {
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val inflater = LayoutInflater.from(parent.context)
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return if (viewType == VIEW_TYPE_USER) {
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UserMessageViewHolder(inflater.inflate(R.layout.item_message_user, parent, false))
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} else {
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AssistantMessageViewHolder(inflater.inflate(R.layout.item_message_assistant, parent, false))
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}
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}
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override fun onBindViewHolder(holder: RecyclerView.ViewHolder, position: Int) {
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holder.itemView.findViewById<TextView>(R.id.msg_content).text = messages[position].content
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}
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override fun getItemCount(): Int = messages.size
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class UserMessageViewHolder(view: View) : RecyclerView.ViewHolder(view)
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class AssistantMessageViewHolder(view: View) : RecyclerView.ViewHolder(view)
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companion object {
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private const val VIEW_TYPE_USER = 1
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private const val VIEW_TYPE_ASSISTANT = 2
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}
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}
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```
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Quickly going through the important parts:
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- `Message` is the smallest useful chat piece: one id, the message text, and a flag saying whether it came from the user or the assistant.
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- `getItemViewType(...)` decides which row layout to use for each message.
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- `onCreateViewHolder(...)` inflates either the user bubble or the assistant bubble layout.
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- `onBindViewHolder(...)` writes the current message text into the row.
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- `getItemCount()` tells the `RecyclerView` how many chat rows it should render.

‎content/learning-paths/mobile-graphics-and-gaming/android-ai-chat-lib/add-model-run-5.md‎

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---
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title: Add Model And Run
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weight: 6
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### FIXED, DO NOT MODIFY
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layout: learningpathall
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---
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## Download a Mobile-compatible GGUF
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Before you run you'll need to download a GGUF model file to run. To be mobile compatible, it'll need to run within your test Android phone's memory. A common Android memory size is 8GB, although some modern premium phones have more. Other things will also need to fit in memory, so the model size will need to be noticeably less than 8GB.
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A good example model is [google_gemma-3-4b-it-Q4_0.gguf](https://huggingface.co/bartowski/google_gemma-3-4b-it-GGUF/blob/main/google_gemma-3-4b-it-Q4_0.gguf). Gemma 3 is a powerful model, and this 4 billion parameter version has been int4 quantized with the Q4_0 schema that works particularly well with Arm's [KleidiAI library](https://developer.arm.com/ai/kleidi-libraries), enabling speed-ups on phones with [SME2](https://www.arm.com/technologies/sme2), [SVE2](https://developer.arm.com/documentation/102340/0100/Introducing-SVE2) and [Neon](https://www.arm.com/technologies/neon).
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Download Gemma 3 or another suitable model onto your phone, ready to run the app.
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## Run the App!
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In Android Studio, if you connect your test Android phone with a USB cable to your computer, you should now be able to run your LLM chatbot app. Make sure when you connect the phone it is in Developer Mode and you allow USB debugging.
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In the bottom right there is a button "Import model". Clicking this will take you to downloads to be able to select the model you've downloaded, so the app can download it. Once it has finished copying and loading the model it will say "Model ready" at the top of the screen. Now if you click the text entry area at the bottom, you can type your questions and chat with the LLM.
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![App screenshot#center](app_screenshot.jpg "Figure 1. AI Chat app screenshot interacting with Gemma 3 4B")

‎content/learning-paths/mobile-graphics-and-gaming/android-ai-chat-lib/app_screenshot.jpg‎

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