llamadart 0.2.0
llamadart: ^0.2.0 copied to clipboard
A Dart/Flutter plugin for llama.cpp - run LLM inference on any platform using GGUF models
0.2.0+b7883 #
- Project Rebrand: Renamed package from
llama_darttollamadart. - Pure Native Assets: Migrated to the modern Dart Native Assets mechanism (
hook/build.dart). - Zero Setup: Native binaries are now automatically downloaded and bundled at runtime based on the target platform and architecture.
- Version Alignment: Aligned package versioning and binary distribution with
llama.cpprelease tags (starting withb7883). - Logging Control: Implemented comprehensive logging interception for both
llamaandggmlbackends with configurable log levels. - Performance Optimization: Added token caching to message processing, significantly reducing latency in long conversations.
- Architecture Overhaul:
- Refactored Flutter Chat Example into a clean, layered architecture (Models, Services, Providers, Widgets).
- Rebuilt CLI Basic Example into a robust conversation tool with interactive and single-response modes.
- Cross-Platform GPU: Verified and improved hardware acceleration on macOS/iOS (Metal) and Android/Linux/Windows (Vulkan).
- New Build System: Consolidated all native source and build infrastructure into a unified
third_party/directory. - Windows Support: Added robust MinGW + Vulkan cross-compilation pipeline.
- UI Enhancements: Added fine-grained rebuilds using Selectors and isolated painting with RepaintBoundaries.
0.1.0 #
- WASM Support: Full support for running the Flutter app and LLM inference in WASM on the web.
- Performance Improvements: Optimized memory usage and loading times for web models.
- Enhanced Web Interop: Improved
wllamaintegration with better error handling and progress reporting. - Bug Fixes: Resolved minor UI issues on mobile and web layouts.
0.0.1 #
- Initial release.
- Supported platforms: iOS, macOS, Android, Linux, Windows, Web.
- Features:
- Text generation with
llama.cppbackend. - GGUF model support.
- Hardware acceleration (Metal, Vulkan).
- Flutter Chat Example.
- CLI Basic Example.
- Text generation with