352 lines
14 KiB
Markdown
352 lines
14 KiB
Markdown
# Jan - Turn your computer into an AI computer
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<p align="center">
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<!-- ALL-CONTRIBUTORS-BADGE:START - Do not remove or modify this section -->
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<img alt="GitHub commit activity" src="https://img.shields.io/github/commit-activity/m/janhq/jan"/>
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<img alt="Github Last Commit" src="https://img.shields.io/github/last-commit/janhq/jan"/>
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<img alt="Github Contributors" src="https://img.shields.io/github/contributors/janhq/jan"/>
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<img alt="GitHub closed issues" src="https://img.shields.io/github/issues-closed/janhq/jan"/>
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<img alt="Discord" src="https://img.shields.io/discord/1107178041848909847?label=discord"/>
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</p>
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<p align="center">
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<a href="https://jan.ai/guides">Getting Started</a>
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- <a href="https://jan.ai/docs">Docs</a>
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- <a href="https://github.com/janhq/jan/releases">Changelog</a>
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- <a href="https://github.com/janhq/jan/issues">Bug reports</a>
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- <a href="https://discord.gg/AsJ8krTT3N">Discord</a>
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</p>
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> [!Warning] >**Jan is currently in Development**: Expect breaking changes and bugs!
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Jan is an open-source ChatGPT alternative that runs 100% offline on your computer.
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**Jan runs on any hardware.** From PCs to multi-GPU clusters, Jan supports universal architectures:
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- [x] NVIDIA GPUs (fast)
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- [x] Apple M-series (fast)
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- [x] Apple Intel
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- [x] Linux Debian
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- [x] Windows x64
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## Download
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<table>
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<tr style="text-align:center">
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<td style="text-align:center"><b>Version Type</b></td>
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<td style="text-align:center"><b>Windows</b></td>
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<td colspan="2" style="text-align:center"><b>MacOS</b></td>
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<td colspan="2" style="text-align:center"><b>Linux</b></td>
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</tr>
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<tr style="text-align:center">
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<td style="text-align:center"><b>Stable (Recommended)</b></td>
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<td style="text-align:center">
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<a href='https://app.jan.ai/download/latest/win-x64'>
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<img src='https://github.com/janhq/jan/blob/dev/docs/static/img/windows.png' style="height:14px; width: 14px" />
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<b>jan.exe</b>
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</a>
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</td>
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<td style="text-align:center">
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<a href='https://app.jan.ai/download/latest/mac-x64'>
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<img src='https://github.com/janhq/jan/blob/dev/docs/static/img/mac.png' style="height:15px; width: 15px" />
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<b>Intel</b>
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</a>
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</td>
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<td style="text-align:center">
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<a href='https://app.jan.ai/download/latest/mac-arm64'>
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<img src='https://github.com/janhq/jan/blob/dev/docs/static/img/mac.png' style="height:15px; width: 15px" />
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<b>M1/M2/M3/M4</b>
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</a>
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</td>
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<td style="text-align:center">
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<a href='https://app.jan.ai/download/latest/linux-amd64-deb'>
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<img src='https://github.com/janhq/jan/blob/dev/docs/static/img/linux.png' style="height:14px; width: 14px" />
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<b>jan.deb</b>
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</a>
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</td>
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<td style="text-align:center">
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<a href='https://app.jan.ai/download/latest/linux-amd64-appimage'>
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<img src='https://github.com/janhq/jan/blob/dev/docs/static/img/linux.png' style="height:14px; width: 14px" />
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<b>jan.AppImage</b>
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</a>
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</td>
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</tr>
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<tr style="text-align:center">
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<td style="text-align:center"><b>Experimental (Nightly Build)</b></td>
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<td style="text-align:center">
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<a href='https://app.jan.ai/download/nightly/win-x64'>
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<img src='https://github.com/janhq/jan/blob/dev/docs/static/img/windows.png' style="height:14px; width: 14px" />
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<b>jan.exe</b>
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</a>
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</td>
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<td style="text-align:center">
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<a href='https://app.jan.ai/download/nightly/mac-x64'>
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<img src='https://github.com/janhq/jan/blob/dev/docs/static/img/mac.png' style="height:15px; width: 15px" />
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<b>Intel</b>
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</a>
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</td>
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<td style="text-align:center">
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<a href='https://app.jan.ai/download/nightly/mac-arm64'>
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<img src='https://github.com/janhq/jan/blob/dev/docs/static/img/mac.png' style="height:15px; width: 15px" />
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<b>M1/M2/M3/M4</b>
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</a>
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</td>
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<td style="text-align:center">
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<a href='https://app.jan.ai/download/nightly/linux-amd64-deb'>
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<img src='https://github.com/janhq/jan/blob/dev/docs/static/img/linux.png' style="height:14px; width: 14px" />
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<b>jan.deb</b>
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</a>
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</td>
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<td style="text-align:center">
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<a href='https://app.jan.ai/download/nightly/linux-amd64-appimage'>
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<img src='https://github.com/janhq/jan/blob/dev/docs/static/img/linux.png' style="height:14px; width: 14px" />
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<b>jan.AppImage</b>
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</a>
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</td>
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</tr>
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</table>
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Download the latest version of Jan at https://jan.ai/ or visit the **[GitHub Releases](https://github.com/janhq/jan/releases)** to download any previous release.
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## Demo
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_Realtime Video: Jan v0.4.3-nightly on a Mac M1, 16GB Sonoma 14_
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## Quicklinks
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#### Jan
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- [Jan website](https://jan.ai/)
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- [Jan GitHub](https://github.com/janhq/jan)
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- [User Guides](https://jan.ai/guides/)
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- [Developer docs](https://jan.ai/developer/)
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- [API reference](https://jan.ai/api-reference/)
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- [Specs](https://jan.ai/docs/)
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#### Nitro
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Nitro is a high-efficiency C++ inference engine for edge computing. It is lightweight and embeddable, and can be used on its own within your own projects.
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- [Nitro Website](https://nitro.jan.ai)
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- [Nitro GitHub](https://github.com/janhq/nitro)
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- [Documentation](https://nitro.jan.ai/docs)
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- [API Reference](https://nitro.jan.ai/api-reference)
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## Troubleshooting
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As Jan is in development mode, you might get stuck on a broken build.
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To reset your installation:
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1. Use the following commands to remove any dangling backend processes:
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```sh
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ps aux | grep nitro
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```
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Look for processes like "nitro" and "nitro_arm_64," and kill them one by one with:
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```sh
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kill -9 <PID>
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```
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2. **Remove Jan from your Applications folder and Cache folder**
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```bash
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make clean
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```
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This will remove all build artifacts and cached files:
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- Delete Jan extension from your `~/jan/extensions` folder
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- Delete all `node_modules` in current folder
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- Clear Application cache in `~/Library/Caches/jan`
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## Requirements for running Jan
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- MacOS: 13 or higher
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- Windows:
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- Windows 10 or higher
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- To enable GPU support:
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- Nvidia GPU with CUDA Toolkit 11.7 or higher
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- Nvidia driver 470.63.01 or higher
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- Linux:
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- glibc 2.27 or higher (check with `ldd --version`)
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- gcc 11, g++ 11, cpp 11 or higher, refer to this [link](https://jan.ai/guides/troubleshooting/gpu-not-used/#specific-requirements-for-linux) for more information
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- To enable GPU support:
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- Nvidia GPU with CUDA Toolkit 11.7 or higher
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- Nvidia driver 470.63.01 or higher
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## Contributing
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Contributions are welcome! Please read the [CONTRIBUTING.md](CONTRIBUTING.md) file
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### Pre-requisites
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- node >= 20.0.0
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- yarn >= 1.22.0
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- make >= 3.81
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### Instructions
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1. **Clone the repository and prepare:**
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```bash
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git clone https://github.com/janhq/jan
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cd jan
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git checkout -b DESIRED_BRANCH
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```
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2. **Run development and use Jan Desktop**
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```bash
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make dev
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```
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This will start the development server and open the desktop app.
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3. (Optional) **Run the API server without frontend**
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```bash
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yarn dev:server
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```
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### For production build
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```bash
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# Do steps 1 and 2 in the previous section
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# Build the app
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make build
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```
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This will build the app MacOS m1/m2 for production (with code signing already done) and put the result in `dist` folder.
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### Docker mode
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- Supported OS: Linux, WSL2 Docker
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- Pre-requisites:
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- Docker Engine and Docker Compose are required to run Jan in Docker mode. Follow the [instructions](https://docs.docker.com/engine/install/ubuntu/) below to get started with Docker Engine on Ubuntu.
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```bash
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curl -fsSL https://get.docker.com -o get-docker.sh
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sudo sh ./get-docker.sh --dry-run
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```
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- If you intend to run Jan in GPU mode, you need to install `nvidia-driver` and `nvidia-docker2`. Follow the instruction [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) for installation.
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- Run Jan in Docker mode
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> User can choose between `docker-compose.yml` with latest prebuilt docker image or `docker-compose-dev.yml` with local docker build
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| Docker compose Profile | Description |
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| ---------------------- | -------------------------------------------- |
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| `cpu-fs` | Run Jan in CPU mode with default file system |
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| `cpu-s3fs` | Run Jan in CPU mode with S3 file system |
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| `gpu-fs` | Run Jan in GPU mode with default file system |
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| `gpu-s3fs` | Run Jan in GPU mode with S3 file system |
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| Environment Variable | Description |
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| ----------------------- | ------------------------------------------------------------------------------------------------------- |
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| `S3_BUCKET_NAME` | S3 bucket name - leave blank for default file system |
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| `AWS_ACCESS_KEY_ID` | AWS access key ID - leave blank for default file system |
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| `AWS_SECRET_ACCESS_KEY` | AWS secret access key - leave blank for default file system |
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| `AWS_ENDPOINT` | AWS endpoint URL - leave blank for default file system |
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| `AWS_REGION` | AWS region - leave blank for default file system |
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| `API_BASE_URL` | Jan Server URL, please modify it as your public ip address or domain name default http://localhost:1377 |
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- **Option 1**: Run Jan in CPU mode
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```bash
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# cpu mode with default file system
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docker compose --profile cpu-fs up -d
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# cpu mode with S3 file system
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docker compose --profile cpu-s3fs up -d
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```
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- **Option 2**: Run Jan in GPU mode
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- **Step 1**: Check CUDA compatibility with your NVIDIA driver by running `nvidia-smi` and check the CUDA version in the output
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```bash
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nvidia-smi
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# Output
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+---------------------------------------------------------------------------------------+
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| NVIDIA-SMI 531.18 Driver Version: 531.18 CUDA Version: 12.1 |
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|-----------------------------------------+----------------------+----------------------+
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| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
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| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
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|=========================================+======================+======================|
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| 0 NVIDIA GeForce RTX 4070 Ti WDDM | 00000000:01:00.0 On | N/A |
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| 0% 44C P8 16W / 285W| 1481MiB / 12282MiB | 2% Default |
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+-----------------------------------------+----------------------+----------------------+
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| 1 NVIDIA GeForce GTX 1660 Ti WDDM | 00000000:02:00.0 Off | N/A |
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| 0% 49C P8 14W / 120W| 0MiB / 6144MiB | 0% Default |
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+-----------------------------------------+----------------------+----------------------+
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| 2 NVIDIA GeForce GTX 1660 Ti WDDM | 00000000:05:00.0 Off | N/A |
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| 29% 38C P8 11W / 120W| 0MiB / 6144MiB | 0% Default |
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+-----------------------------------------+----------------------+----------------------+
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+---------------------------------------------------------------------------------------+
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| Processes: |
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| GPU GI CI PID Type Process name GPU Memory |
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| ID ID Usage |
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|=======================================================================================|
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```
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- **Step 2**: Visit [NVIDIA NGC Catalog ](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/cuda/tags) and find the smallest minor version of image tag that matches your CUDA version (e.g., 12.1 -> 12.1.0)
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- **Step 3**: Update the `Dockerfile.gpu` line number 5 with the latest minor version of the image tag from step 2 (e.g. change `FROM nvidia/cuda:12.2.0-runtime-ubuntu22.04 AS base` to `FROM nvidia/cuda:12.1.0-runtime-ubuntu22.04 AS base`)
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- **Step 4**: Run command to start Jan in GPU mode
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```bash
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# GPU mode with default file system
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docker compose --profile gpu-fs up -d
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# GPU mode with S3 file system
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docker compose --profile gpu-s3fs up -d
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```
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This will start the web server and you can access Jan at `http://localhost:3000`.
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> Note: RAG feature is not supported in Docker mode with s3fs yet.
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## Acknowledgements
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Jan builds on top of other open-source projects:
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- [llama.cpp](https://github.com/ggerganov/llama.cpp)
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- [LangChain](https://github.com/langchain-ai)
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- [TensorRT](https://github.com/NVIDIA/TensorRT)
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- [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM)
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## Contact
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- Bugs & requests: file a GitHub ticket
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- For discussion: join our Discord [here](https://discord.gg/FTk2MvZwJH)
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- For business inquiries: email hello@jan.ai
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- For jobs: please email hr@jan.ai
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## Trust & Safety
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Beware of scams.
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- We will never ask you for personal info
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- We are a free product; there's no paid version
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- We don't have a token or ICO
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- We are not actively fundraising or seeking donations
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## License
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Jan is free and open source, under the AGPLv3 license.
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