Introduction to LlamaChat
LlamaChat is a macOS application designed to enable users to engage in conversations with popular machine learning models directly on their computers. It supports a variety of models including LLaMA, Alpaca, and GPT4All, all running locally on a Mac without the need for cloud-based computation.
Getting Started
To use LlamaChat, users need to have macOS 13 Ventura installed on either an Intel or Apple Silicon processor. The app can be easily downloaded as a .dmg file from the official website. Additionally, for those interested in exploring the code or personalizing the app's functionalities, LlamaChat can be built from source using simple git commands and Xcode.
Features
- Supported Models: Initially, LlamaChat supports LLaMA, Alpaca, and GPT4All models, with plans to include models like Vicuna and Koala. The developers are also working on incorporating support for Chinese and French language models.
- Flexible Model Formats: The app is designed to be highly adaptable, allowing developers to add models in various formats like
.pthand.ggml. - Model Conversion: If users have raw PyTorch model checkpoints, LlamaChat can convert these into the
.ggmlformat, which is necessary for app compatibility. - Chat History and Avatars: The app not only saves chat history for future reference but also offers fun avatars to enhance user experience.
- Advanced Features for Developers: LlamaChat includes advanced features such as context debugging, which is geared towards machine learning enthusiasts who wish to delve deeper into model behavior during interactions.
Models
LlamaChat does not come with model files pre-installed, so users must obtain the models separately, adhering to the terms set by the respective model creators. Users can import models in Python checkpoint form or use pre-converted .ggml files suited for LlamaChat.
Troubleshooting
Models in .ggml format need to be current, as outdated files may cause issues. If conversion problems occur, users may need to employ script tools like those provided in the llama.cpp repository to adjust their models accordingly.
Contributing
LlamaChat welcomes contributors to improve and expand its functionalities. Built completely in Swift and SwiftUI, the project uses an MVVM architecture, leveraging Swift’s Combine framework and concurrency features. Contributions should adhere to the project's Code of Conduct.
License
LlamaChat is available under the MIT license, encouraging wide use and further development from the community.