Making cross-platform local AI easier with llamadart
My writing assistant could talk to Gemini. The missing piece was using it without a connection. That was the reason I started llamadart: I wanted an offline mode for flights, unreliable internet, and environments where outbound API access was unavailable. In my first article , I focused on the work needed to get there: native binaries, Dart build hooks, and model chat templates. Getting a…
The article "<source 1b2a2df4-d10>" focuses on the improvements made to the llamadart project, making it easier to use local AI for cross-platform applications. The primary goal of llamadart is to provide an offline mode for scenarios with unreliable internet connections or unavailable outbound API access.
The author highlights that getting a response from a local model is a significant milestone and leads to numerous application problems. These include the origin of the model, the consequences of a canceled download, conversation storage, and the ability to switch models without losing the currently functional one. The changes implemented in llamadart version 0.11 address these concerns by streamlining the integration work and simplifying the API.
The author walks through an illustrative app flow to demonstrate the usage of the new features. This flow includes downloading a model, asking it to rewrite a paragraph, and requesting a shorter version. The article emphasizes that the example is for demonstration purposes and not a claim about a particular model's writing quality.
Before the first answer, the article discusses the process of adding an "Offline mode" button to the application. This button triggers a download, displays progress, and handles recovery when the user closes the screen. The native packaging work from version 0.10 is still relevant, as app developers don't require a local C++ toolchain for common setup. The build hook in the package resolves native runtime assets.
Model files are handled separately in version 0.11. The model-loading entrypoint now combines model files, simplifying the process. A LlamaModel describes the model and an optional multimodal projector, with its ModelSource able to be a local path, URL, or Hugging Face reference. This change has brought the engine and backend creation closer to the caller, making ownership clearer and enabling progress and cancellation to be presented through onProgress and download options.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
