Open Source Dart Artificial Intelligence Software

Maid is a cross-platform Flutter app for interfacing with GGUF / llama.cpp models locally, and with Ollama and OpenAI models remotely. Maid is a cross-platform free and open source application for interfacing with llama.cpp models locally, and remotely with Ollama, Mistral, Google Gemini and OpenAI models remotely. Maid supports Sillytavern character cards to allow you to interact with all your favorite characters. Maid supports downloading a curated list of Models in-app directly from hugging face.

Reins is a privacy-first, multi-platform AI client designed to simplify and enhance interaction with Ollama-based language models. It provides a highly customizable chat interface where users can configure system prompts, switch models dynamically, and adjust inference parameters such as temperature, token limits, and context size on a per-conversation basis. The application is built to run across platforms including mobile and desktop environments, making it accessible for a wide range of users who want consistent control over their AI workflows. It also includes features for editing and regenerating messages, enabling iterative refinement of outputs without restarting conversations. Reins extends beyond text by supporting image input and multimodal interactions, which expands its use cases beyond basic chat scenarios. Overall, it is best suited for users who want granular control over model behavior and experimentation while maintaining a clean and intuitive interface.

ChatMCP is a cross‑platform AI chat client that implements the Model Context Protocol (MCP) to provide unified chat experiences across environments—including desktop, mobile, and web—with synchronization and protocol support tailored for MCP. You can install MCP Server from MCP Server Market, MCP Server Market is a collection of MCP Server, you can use it to chat with different data. Tested on major distributions: Ubuntu, Fedora, Arch Linux, openSUSE. Improved Experience: Latest versions include better dark theme support, unified data storage following XDG Base Directory Specification, and an optimized UI layout for Linux desktop environments is planned.

ConfiChat is a lightweight, privacy-focused chat interface designed to give users full control over their interaction with large language models across both local and cloud providers. Built as a standalone application without heavy dependencies, it emphasizes simplicity, portability, and ease of setup across multiple platforms including desktop and mobile environments. The tool supports local models such as Ollama and llama.cpp for fully offline operation, while also allowing integration with cloud APIs like OpenAI and Anthropic for access to more advanced capabilities. A key differentiator is its optional encryption of chat history and assets, ensuring that sensitive data can remain secure even when stored locally. Conversations are managed as local JSON files, giving users transparency and direct control over their data. Overall, ConfiChat is designed for users who prioritize privacy, flexibility, and independence from complex infrastructure while still maintaining access.

The Omi project is an open-source AI wearable ecosystem developed by Based Hardware that combines hardware, software, and cloud infrastructure to create a persistent “second brain” for capturing and processing real-world interactions. It is designed as a system that continuously listens to conversations and monitors screen activity, converting this input into structured data such as transcripts, summaries, and actionable insights in real time. The platform operates across multiple environments, including wearable devices, mobile apps, and desktop applications, ensuring seamless integration into a user’s daily workflow. At its core, omi uses a pipeline of speech-to-text systems, large language models, and memory storage services to transform raw audio and context into meaningful outputs like tasks and reminders. The architecture is modular and extensible, featuring APIs, SDKs, and plugin-like capabilities that allow developers to build custom applications.

AIdea is a comprehensive Flutter-based cross-platform app integrating major AI models—OpenAI GPT, Chinese models Tongyi Qianwen and Wenxin Yiyan, plus image models like Stable Diffusion for text-to-image, image-to-image, SDXL 1.0, super-resolution, and colorization. It includes a client app, server backend, and Docker deployment scripts for hosted setups.

Glowby is an open-source platform designed to assist users in creating and sharing interactive educational content, enabling collaborative learning experiences.

Short GPT Lite is a simple tool for Windows/Linux based on OpenAI's GPT3/GPT4 large language model. The main focus is to get quick and concise answers from GPT. ShortGPT is now available on Android : https://play.google.com/store/apps/details?id=io.github.rupeshs.shortgpt_lite ShortGPT basic web version is now available try it for free: https://nolowiz.com/shortgpt-get-short-and-concise-answers-from-gpt-for-free/

flutter_ume is an in-app debug-kit platform for Flutter applications, developed by ByteDance’s Flutter Infra team. It lets developers embed a suite of debugging tools directly into a Flutter app (during development or debug builds), enabling inspection, performance monitoring, UI debugging, network request inspection, widget hierarchy introspection, and more — all from within the running app. UME bundles multiple “plugin kits” (e.g., UI inspector, performance monitor, device info panel, network inspector via Dio, console log viewer, code viewer, touch indicator) so developers can enable only the tools they need. It supports Flutter 3 and Dart with null-safety, integrates as a dev dependency (so it doesn’t ship by default with production builds), and offers a simple API to activate the debug overlay. Because it's open source under MIT license, developers can also create custom plugin kits and extend UME’s capabilities to suit their debugging or testing workflow.