janhq / jan

# Jan - Open-source ChatGPT replacement
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 Getting Started 
 - Community 
 - Changelog 
 - Bug reports 
Jan is bringing the best of open-source AI in an easy-to-use product. Download and run LLMs with **full control** and **privacy**.
## Installation
The easiest way to get started is by downloading one of the following versions for your respective operating system:
 Platform 
 Download 
 Windows 
 jan.exe 
 macOS 
 jan.dmg 
 Linux (deb) 
 jan.deb 
 Linux (AppImage) 
 jan.AppImage 
 Linux (Arm64) 
 How-to 
Download from jan.ai or GitHub Releases.
## Features
- **Local AI Models**: Download and run LLMs (Llama, Gemma, Qwen, GPT-oss etc.) from HuggingFace
- **Cloud Integration**: Connect to GPT models via OpenAI, Claude models via Anthropic, Mistral, Groq, MiniMax, and others
- **Custom Assistants**: Create specialized AI assistants for your tasks
- **OpenAI-Compatible API**: Local server at `localhost:1337` for other applications
- **Model Context Protocol**: MCP integration for agentic capabilities
- **Privacy First**: Everything runs locally when you want it to
## Build from Source
For those who enjoy the scenic route:
### Prerequisites
- Node.js ≥ 20.0.0
- Yarn ≥ 4.5.3
- Make ≥ 3.81
- Rust (for Tauri)
- (macOS Apple Silicon only) MetalToolchain `xcodebuild -downloadComponent MetalToolchain`
### Run with Make
 [code] 
This handles everything: installs dependencies, builds core components, and launches the app.
**Available make targets:**
- `make dev` - Full development setup and launch
- `make build` - Production build
- `make test` - Run tests and linting
- `make clean` - Delete everything and start fresh
### Manual Commands
 [code] 
### Building on Windows
Run `make dev` from **Git Bash** (installed with Git for Windows) — make dispatches its recipes through `sh`, so a plain `cmd.exe` won't work.
You do **not** need a "Native Tools Command Prompt for VS 2022". The bundled llama.cpp engine builds with Ninja + `clang-cl`, and `clang-cl` locates the MSVC toolchain and Windows SDK on its own. What has to be installed (and on `PATH` for `ninja`/`clang-cl`/`cmake`):
- Visual Studio 2022 Build Tools (MSVC x64 workload + Windows SDK)
- LLVM (provides `clang-cl`)
- Ninja
- CMake
- CUDA Toolkit — only for `JAN_ENGINE_VARIANT=cuda12`/`cuda13` builds
Engine variants are picked with `JAN_ENGINE_VARIANT` (tokens: `cpu`, `vulkan`, `metal`, `cuda12`, `cuda13`, `hip`/`rocm`, joined by `-`), e.g.:
 [code] 
**"nvcc fatal : Could not open output file ...fattn-...cu.obj.d"** during `tauri-plugin-llamacpp(build)` means the build path crossed Windows' 260-character `MAX_PATH` limit — nvcc does not honor the long-path opt-in. The build script now detects this and automatically relocates the llama.cpp build tree to a short directory under `%LOCALAPPDATA%\jan-engine`. If you hit path-length errors anyway, set `JAN_ENGINE_BUILD_DIR` to a short path (e.g. `C:\jb`) or move the checkout closer to the drive root.
## System Requirements
**Minimum specs fo