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A fast, lightweight, and extensible RWKV chat UI powered by Flutter. Offline-ready, multi-backend support, ideal for local RWKV inference.

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RWKV App ✨

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Explore and experience running Large Language Models offline on your edge devices with the RWKV App. A privacy-first, fully on-device LLM experience built for everyday devices.

RWKV App is an experimental application that brings Large Language Models (LLMs) directly to your Android/iOS devices. You can experiment with different models, engage in chats, generate speech, perform visual understanding, and more! All computations are performed locally, and no internet connection is required after loading the model.

Overview

The RWKV App supports multi-turn conversations, text-to-speech, visual understanding, and various other tasks.

RWKV App Screenshot

✨ Core Features

  • 📱 Run Locally, Fully Offline: Experience the magic of generative AI without an internet connection. All processing is done directly on your device.
  • 🤖 Switch Models Freely: Easily download and switch between different models from Hugging Face to compare their performance.
  • 💬 AI Chat: Engage in fluent multi-turn conversations.
  • 🔊 Text-to-Speech (TTS): Convert text into natural-sounding speech.
  • 🖼️ Visual Understanding: Explore image-based AI use cases.
  • 🌓 Dark Mode: Supports comfortable use in various lighting conditions.

🧭 Download and Experience

Downloads

Official Download Page: https://rwkv.halowang.cloud/

RWKV Chat (with See and Talk) RWKV Sudoku RWKV Othello RWKV Music (Another repo)
Android APK Download Link Google Play / GitHub Release / huggingface / pgyer huggingface / pgyer huggingface / pgyer pgyer
iOS App Store / testflight - testflight -
Windows GitHub Release / huggingface (zip) / huggingface (installer) / QQ Group / Discord Microsoft Store
macOS GitHub Release / huggingface / QQ Group / Discord -
Linux GitHub Release / huggingface - - -

Note

In the future, we will integrate all separate features into the RWKV Chat app to provide a unified experience.

Usage

When you first open the app, a model selection panel will appear. Please choose the model weights you want to use based on your needs.

Warning

Devices older than the iPhone 14 may not be able to smoothly run models with 1.5B / 2.9B parameters.

💻 Development

Ensure you have the Flutter development environment set up.

  1. Clone the repository:
# MUST switch to the 'dev' branch
git clone -b dev https://github.com/MollySophia/rwkv_mobile_flutter.git
# Make sure the rwkv_mobile_flutter and RWKV_APP are in the same directory
git clone -b dev https://github.com/RWKV-APP/RWKV_APP.git
cd RWKV_APP
  1. Create necessary configuration files:
touch assets/filter.txt;touch .env;
  1. Install dependencies:
flutter pub get
  1. (Optional) Install dependencies for the tools directory:

Doing this avoids the “Errors exist in your project” warning in VS Code and Cursor when you run the app.

cd tools; flutter pub get; cd ..;
  1. Run the application:
flutter run

🛠️ Technical Highlights

  • Flutter: An open-source framework for building cross-platform user interfaces, supporting Android, iOS, Windows, and macOS.
  • Dart FFI (Foreign Function Interface): Used for efficient communication between Dart and the C++ inference engine.
  • C++ Inference Engine: The core on-device inference engine, built with C++, supporting multiple model formats and hardware acceleration (CPU/GPU/NPU).
  • Hugging Face: An open-source community providing models, datasets, and tools; used here as the source for model weights.

🗺️ Roadmap

  • Integrate all features into the RWKV Chat app
  • Support more model weights
  • Support more hardware
  • Support more operating systems
  • Support more devices (e.g., watches, VR glasses)

🤝 Feedback and Contribution

This is an experimental early-stage version, and your feedback is crucial to us!

📄 License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.

🔗 Related Links

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A fast, lightweight, and extensible RWKV chat UI powered by Flutter. Offline-ready, multi-backend support, ideal for local RWKV inference.

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