Jan - Run your own AI

Getting Started - Docs - Changelog - Bug reports - Discord

⚠️ Jan is currently in Development: Expect breaking changes and bugs!

Jan lets you run AI on your own hardware, with helpful tools to manage models and monitor your hardware performance.

In the background, Jan runs Nitro, a C++ inference engine. It runs various model formats (GGUF/TensorRT) on various hardware (Mac M1/M2/Intel, Windows, Linux, and datacenter-grade Nvidia GPUs) with optional GPU acceleration.

See the Nitro codebase at https://nitro.jan.ai.

Demo

Quicklinks

• Developer documentation: https://jan.ai/docs (Work in Progress)
• Desktop app: Download at https://jan.ai/
• Mobile app shell: Download via App Store | Android
• Nitro (C++ AI Engine): https://nitro.jan.ai

Plugins

Jan supports core & 3rd party extensions:

• LLM chat: Self-hosted Llama2 and LLMs
• Model Manager: 1-click to install, swap, and delete models
• Storage: Optionally store your conversation history and other data in SQLite/your storage of choice
• 3rd-party AIs: Connect to ChatGPT, Claude via API Key (in progress)
• Cross device support: Mobile & Web support for custom shared servers (in progress)
• File retrieval: User can upload private and run a vectorDB (planned)
• Multi-user support: Share a single server across a team/friends (planned)
• Compliance: Auditing and flagging features (planned)

Hardware Support

Nitro provides both CPU and GPU support, via llama.cpp and TensorRT, respectively.

• Nvidia GPUs (accelerated)
• Apple M-series (accelerated)
• Linux DEB
• Windows x64

Not supported yet: Apple Intel, Linux RPM, Windows x86|ARM64, AMD ROCm

See developer docs for detailed installation instructions.

Installation and Usage

Pre-requisites

• node >= 20.0.0
• yarn >= 1.22.0

Use as complete suite (in progress)

For interactive development

Note: This instruction is tested on MacOS only.

1. Clone the Repository:

   git clone https://github.com/janhq/jan
   git checkout feature/hackathon-refactor-jan-into-electron-app
   cd jan
   

2. Install dependencies:

   yarn install
   
   # Packing base plugins
   yarn build:plugins
   

3. Run development and Using Jan Desktop

   yarn dev
   

   This will start the development server and open the desktop app. In this step, there are a few notification about installing base plugin, just click OK and Next to continue.

For production build

# Do step 1 and 2 in previous section
git clone https://github.com/janhq/jan
cd jan
yarn install
yarn build:plugins

# Build the app
yarn build

This will build the app MacOS m1/m2 for production (with code signing already done) and put the result in dist folder.

Contributing

Contributions are welcome! Please read the CONTRIBUTING.md file

# From the root, run:
yarn install

yarn build:plugins

yarn dev

See developer docs for guidelines on how to contribute to this project.

License

Jan is free, open core, and Sustainable Use Licensed.

Acknowledgements

Jan builds on top of other open-source projects:

• llama.cpp
• TensorRT
• Keycloak Community (Apache-2.0)

Contact

• Bugs & requests: file a Github ticket
• For discussion: join our Discord here
• For business inquiries: email [email protected]
• For jobs: please email [email protected]