Playground

Interactive demo projects showcasing what you can build with RunAnywhere.

Project	Description	Platform
YapRun	On-device voice dictation — custom keyboard, multiple Whisper backends, Live Activity, offline-ready — Website · TestFlight	iOS & macOS (Swift/SwiftUI)
swift-starter-app	Privacy-first AI demo — LLM Chat, Speech-to-Text, Text-to-Speech, and Voice Pipeline with VAD	iOS (Swift/SwiftUI)
on-device-browser-agent	On-device AI browser automation using WebLLM — no cloud, no API keys, fully private	Chrome Extension (TypeScript/React)
android-use-agent	Fully on-device autonomous Android agent — navigates phone UI via accessibility + on-device LLM (Qwen3-4B). See benchmarks	Android (Kotlin/Jetpack Compose)
linux-voice-assistant	Fully on-device voice assistant — Wake Word, VAD, STT, LLM, and TTS with zero cloud dependency	Linux (C++/ALSA)
openclaw-hybrid-assistant	Hybrid voice assistant — on-device Wake Word, VAD, STT, and TTS with cloud LLM via OpenClaw WebSocket	Linux (C++/ALSA)

YapRun

On-device voice dictation for iOS and macOS. All speech recognition runs locally — your voice never leaves your device.

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• Custom Keyboard — Tap "Yap" from any text field in any app to dictate
• Multiple Whisper Backends — WhisperKit (Neural Engine) and ONNX (CPU) with one-tap model switching
• Live Activity — Real-time transcription status on the Lock Screen and Dynamic Island
• ASR Playground — Record and transcribe in-app to test speed and accuracy
• macOS Agent — Menu bar icon, global hotkey dictation, floating flow bar
• Offline-Ready — Download once, run without a network connection

runanywhere.ai/yaprun | TestFlight Beta | Free on the App Store — iOS 16.0+ / macOS 14.0+, Xcode 15.0+

linux-voice-assistant

A complete on-device voice AI pipeline for Linux (Raspberry Pi 5, x86_64, ARM64). All inference runs locally — no cloud, no API keys:

• Wake Word Detection — "Hey Jarvis" activation using openWakeWord (ONNX)
• Voice Activity Detection — Silero VAD with silence timeout
• Speech-to-Text — Whisper Tiny EN via Sherpa-ONNX
• Large Language Model — Qwen2.5 0.5B Q4 via llama.cpp (fully local)
• Text-to-Speech — Piper Lessac Medium neural TTS

Requirements: Linux (ALSA), x86_64 or ARM64, CMake 3.16+, C++20

swift-starter-app

A full-featured iOS app demonstrating the RunAnywhere SDK's core capabilities:

• LLM Chat — On-device conversation with local language models
• Speech-to-Text — Whisper-powered transcription
• Text-to-Speech — Neural voice synthesis
• Voice Pipeline — Integrated STT → LLM → TTS with Voice Activity Detection

Requirements: iOS 17.0+, Xcode 15.0+

on-device-browser-agent

A Chrome extension that automates browser tasks entirely on-device using WebLLM and WebGPU:

• Two-agent architecture — Planner + Navigator for intelligent task execution
• DOM and Vision modes — Text-based or screenshot-based page understanding
• Site-specific handling — Optimized workflows for Amazon, YouTube, and more
• Fully offline — All AI inference runs locally on GPU after initial model download

Requirements: Chrome 124+ (WebGPU support)

android-use-agent

A fully on-device autonomous Android agent that navigates your phone's UI to accomplish tasks. All LLM inference runs locally via RunAnywhere SDK with llama.cpp -- no cloud dependency required.

• Fully On-Device AI — LLM inference via RunAnywhere SDK + llama.cpp (Qwen3-4B recommended)
• Accessibility-Based Screen Parsing — Reads UI tree via Android Accessibility API, no root required
• Tool Calling — LLM outputs structured tool calls (<tool_call> XML or ui_tap(index=5) function-call style)
• Samsung Foreground Boost — 15x inference speedup by bringing agent to foreground during inference
• Smart Pre-Launch — Opens target apps via Android intents before the agent loop
• Optional Cloud Fallback — GPT-4o with vision and function calling when an API key is configured
• Voice Mode — Speak goals via on-device Whisper STT, hear progress via TTS

See android-use-agent/ASSESSMENT.md for detailed model benchmarks across Qwen3-4B, LFM2.5-1.2B, LFM2-8B-A1B MoE, and DS-R1-Qwen3-8B on Samsung Galaxy S24.

Requirements: Android 8.0+ (API 26), arm64-v8a device, Accessibility service permission

openclaw-hybrid-assistant

A hybrid voice assistant that combines on-device AI inference with cloud LLM reasoning via OpenClaw:

• Wake Word Detection — "Hey Jarvis" activation using openWakeWord (ONNX)
• Voice Activity Detection — Silero VAD with noise-robust debouncing and burst filtering
• Speech-to-Text — Parakeet TDT-CTC 110M (NeMo CTC) for fast on-device transcription
• Text-to-Speech — Piper neural TTS with streaming sentence-level pre-synthesis
• OpenClaw Integration — Raw WebSocket client sends transcriptions to cloud LLM, receives responses
• Barge-in Support — Wake word during TTS playback cancels speech and re-listens
• Waiting Chime — Earcon feedback while waiting for cloud response

Requirements: Linux (ALSA), x86_64 or ARM64, CMake 3.16+, C++20