v2.0 modules#

Llamatik 2.0 ships three independent artifacts. Add whichever you need:

dependencies {
    // Core inference layer (required)
    implementation("com.llamatik:core:<version>")

    // SDK — business logic, chat, RAG, Agent Framework (recommended)
    implementation("com.llamatik:sdk:<version>")

    // Agent Platform runtime (optional)
    implementation("com.llamatik:sdk-agent:<version>")
}

Upgrading from 1.x? See the Migration Guide.

Kotlin Multiplatform#

In a KMP project, add the dependencies to the source sets that need them:

kotlin {
    sourceSets {
        val commonMain by getting {
            dependencies {
                implementation("com.llamatik:core:<version>")
                implementation("com.llamatik:sdk:<version>")
            }
        }
    }
}

Platform notes#

Android#

• Min SDK: 26
• The library loads native code at runtime.
• If you package models in assets, make sure your app can resolve or copy them to a readable file path before initialization.

iOS#

• Minimum deployment target: 16.6
• The library is consumed through Kotlin Multiplatform / Kotlin Native integration.
• Model files need to be bundled or downloaded in a way your app can resolve to an actual file path.

JVM / Desktop#

• Use a recent JDK. The repository is configured around toolchain 21.
• Native libraries are loaded from packaged resources.
• Model paths are usually absolute disk paths.

WASM#

• Text generation is available through the WASM implementation.
• Embeddings, Stable Diffusion, Whisper, and KV session persistence are currently not available.
• If you rely on streaming or worker-only execution, prefer the streaming APIs.

What to install beyond the dependency#

Llamatik gives you the native bridge. You still need compatible model files:

• LlamaBridge: GGUF text models, and GGUF embedding models for initEmbedModel
• StableDiffusionBridge: a compatible Stable Diffusion model file
• WhisperBridge: a compatible Whisper model file

The next page explains how to think about model selection.