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On-device LLM inference SDK for Flutter. Run Llama, Phi, and other language models locally with Metal GPU acceleration on iOS devices.

Changelog #

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

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

[Unreleased] #

Planned #

  • Flutter Web support (WASM + WebGPU)
  • Speech-to-Text integration (Whisper)
  • Text-to-Speech integration (Kokoro-82M)
  • Voice Activity Detection (VAD)
  • Prompt caching
  • LoRA adapter support
  • macOS and Windows desktop support

1.0.0 - 2026-02-04 #

Added #

  • Initial release of Edge Veda Flutter SDK
  • On-device LLM inference with llama.cpp integration
  • FFI bindings for native C++ core
  • Hardware acceleration support (Metal on iOS, Vulkan on Android)
  • Streaming text generation with real-time tokens
  • Model download and management system
  • Checksum verification for model integrity
  • Memory-safe operations with configurable limits
  • Pre-configured model registry (Llama 3.2, Phi 3.5, Gemma 2, TinyLlama)
  • Comprehensive error handling with typed exceptions
  • Example chat application
  • Full API documentation

Features #

  • EdgeVeda class for LLM inference
  • ModelManager for downloading and caching models
  • GenerateOptions for fine-grained control
  • Token streaming with TokenChunk
  • Progress tracking for model downloads
  • Memory usage monitoring
  • Support for system prompts and JSON mode
  • Stop sequences for controlled generation

Platform Support #

  • iOS 13.0+ with Metal acceleration
  • Android API 24+ with Vulkan support

Documentation #

  • Complete README with quick start guide
  • API reference documentation
  • Example application
  • Best practices and troubleshooting
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On-device LLM inference SDK for Flutter. Run Llama, Phi, and other language models locally with Metal GPU acceleration on iOS devices.

Repository (GitHub)
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License

unknown (license)

Dependencies

crypto, ffi, flutter, http, path, path_provider

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