runanywhere 0.19.13

Privacy-first, on-device AI SDK for Flutter. Run LLMs, STT, TTS, and VAD directly on device with no data leaving the device.

Changelog

All notable changes to the RunAnywhere Flutter SDK will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

0.19.13 - 2026-05-18

Removed (BREAKING)

• VAD callback API: Removed RunAnywhereVAD.activityStream, setSpeechActivityCallback, setAudioBufferCallback, and setStatisticsCallback. Subscribe to RunAnywhere.vad.streamVAD(audio) instead. This brings the Flutter VAD surface in line with the Swift capability (RunAnywhere+VAD.swift).

Changed

• v2 architecture: All public capability surfaces (RunAnywhere.llm, .stt, .tts, .vad, .vlm, .voice, .embeddings, .tools, .rag, .models, .modelLifecycle, .downloads, .hardware, .solutions, .lora) are now namespaced accessors on the RunAnywhere static entry point, mirroring the Swift/Kotlin/RN/Web SDKs.
• Lifecycle-owned LLM/STT/TTS/VLM loads: Model loading now routes through commons model lifecycle via the generated proto ABIs (rac_*_lifecycle_proto). Per-component handle ownership has moved into C++.
• Public Voice eventStream(): Voice agent surface now exposes a proto-typed eventStream mirroring Swift's RunAnywhere.voice.events.
• Tool-calling session ABIs: Tool-calling now uses session-based proto requests (rac_tool_calling_*_proto) for parity with Swift/Kotlin.
• Plugin loader capability: New RunAnywherePluginLoader surface for registering backend plugins (LlamaCpp/ONNX/QHexRT) from Dart.
• Model lifecycle / registry split: RunAnywhereModels (registry) and RunAnywhereModelLifecycle (load/unload/current) are now separate capability classes.
• Convenience codegen: Added generated *.defaults() factories (VADConfiguration.defaults(), LLMOptions.defaults(), etc.) so callers no longer hand-construct proto messages with magic defaults.

0.17.0 - 2026-03-09

Added

• QHexRT NPU Backend: Added NPU framework enum support for Qualcomm Hexagon bundles
• RAG Types: Extended RAG type definitions for enhanced retrieval-augmented generation

Changed

• Updated model type definitions to support NPU framework registration

0.16.0 - 2026-02-14

Added

• API Configuration: Custom API configuration management for flexible backend routing
• Keychain Store: Secure credential storage capabilities via platform keychain
• Dev Mode: Development configuration support for local testing and debugging

Fixed

• Parameter Piping: Fixed parameter propagation through SDK layers (#340)
• Network Layer: Resolved authentication and dev config networking issues
• Simulator Scripts: Fixed build scripts for iOS simulator targets
• Android Models: Updated model support handling for Android platform

Changed

• Updated native binaries (RACommons, RABackendLLAMACPP, RABackendONNX) to latest builds
• Addressed PR #309 review feedback with critical fixes

0.15.11 - 2025-01-11

Fixed

• iOS: Updated RACommons.xcframework to v0.1.5 with correct symbol visibility
  • The v0.1.4 xcframework had symbols that became local during linking
  • v0.1.5 xcframework properly exports all symbols as global
  • Combined with DynamicLibrary.executable() from 0.15.10, iOS now works correctly

0.15.10 - 2025-01-11

Fixed

• iOS: Fixed symbol lookup by using DynamicLibrary.executable() instead of DynamicLibrary.process()
  • process() uses dlsym(RTLD_DEFAULT) which only finds GLOBAL symbols
  • executable() can find both global and LOCAL symbols in the main binary
  • With static linkage, xcframework symbols become local - this is the correct fix

0.15.9 - 2025-01-11

Fixed

• iOS: Added linker flags (partial fix, superseded by 0.15.10)

Important

• iOS Podfile Configuration Required: Users must configure their Podfile with use_frameworks! :linkage => :static for the SDK to work correctly. See README.md for complete setup instructions.

0.15.8 - 2025-01-10

Added

• Initial public release on pub.dev
• Core SDK infrastructure with modular backend support
• Event bus for component communication
• Service container for dependency injection
• Native FFI bridge for on-device AI inference
• Audio capture and playback management
• Model download and management system
• Voice session management
• Structured output handling for LLM responses

Features

• Speech-to-Text (STT) interface
• Text-to-Speech (TTS) interface with system TTS fallback
• Voice Activity Detection (VAD) interface
• LLM text generation interface with streaming support
• Voice agent orchestration
• Secure storage for API keys and credentials

Platforms

• iOS 13.0+ support
• Android API 24+ support