janhq · henryh0x1 · Nov 22, 2023 · Nov 20, 2023 · Nov 20, 2023 · Nov 20, 2023
diff --git a/docs/docs/install/from-source.md b/docs/docs/install/from-source.md
@@ -0,0 1,64 @@
 ---
 title: From Source
 ---
 
 # Install Jan from Source
 
 ## Installation
 
 ### Pre-requisites
 Before proceeding with the installation of Jan from source, ensure that the following software versions are installed on your system:
 - Node.js version 20.0.0 or higher 
 - Yarn version 1.22.0 or higher
 
 ### Instructions
 > **_Note:_** This instruction is tested on MacOS only.
 
 1. Clone the Jan repository from GitHub
 ```bash
 git clone https://github.com/janhq/jan
 git checkout DESIRED_BRANCH
 cd jan
 ```
 2. Install the required dependencies using Yarn
 ```bash
 yarn install
 
 # Build core module
 yarn build:core
 
 # Packing base plugins
 yarn build:plugins
 
 # Packing uikit
 yarn build:uikit
 ```
 3. Run development and using Jan
 ```bash
 yarn dev
 ```
 This will start the development server and open the desktop app. During this step, you may encounter notifications about installing base plugins. Simply click `OK` and `Next` to continue.
 
 #### For production build
 Build the app for macOS M1/M2 for production and place the result in the dist folder
 
 ```bash
 # Do step 1 and 2 in previous section
 git clone https://github.com/janhq/jan
 cd jan
 yarn install
 
 # Build core module
 yarn build:core
 
 # Package base plugins
 yarn build:plugins
 
 # Packing uikit
 yarn build:uikit
 
 # Build the app
 yarn build
 ```
 
 This completes the installation process for Jan from source. The production-ready app for macOS can be found in the dist folder.
diff --git a/docs/docs/install/linux.md b/docs/docs/install/linux.md
@@ -2,76 2,21 @@
 title: Linux
 ---
 
-# Installing Jan on Linux
 # Jan on Linux
 
 ## Installation
 
-### Step 1: Download the Installer
-To begin using 👋Jan.ai on your Windows computer, follow these steps:
-
-1. Visit [Jan.ai](https://jan.ai/).
-2. Click on the "Download for Windows" button to download the Jan Installer.
-
-![Jan Installer](/img/jan-download.png)
-
-:::tip
-
-For faster results, you should enable your NVIDIA GPU. Make sure to have the CUDA toolkit installed. You can download it from your Linux distro's package manager or from here: [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads).
-
-:::
-
 1. To download the lastest version of Jan on Linux, please visit the [Jan's homepage](https://jan.ai/).
 2. For Debian/Ubuntu-based distributions, the recommended installation method is through the `.deb` package (64-bit). This can be done either through the graphical software center, if available, or via the command line using the following:
 ```bash
-apt install nvidia-cuda-toolkit
 sudo apt install ./jan-linux-amd64-<version>.deb
 # sudo apt install ./jan-linux-arm64-0.3.1.deb
 ```
 
-Check the installation by
-
 ## Uninstall Jan
 To uninstall VS Code on Linux, you should use your package manager's uninstall or remove option. For Debian/Ubuntu-based distributions, if you installed Jan via the `.deb` package, you can uninstall Jan using the following command:
 ```bash
-nvidia-smi
-```
-
-:::tip
-
-For AMD GPU. You can download it from your Linux distro's package manager or from here: [ROCm Quick Start (Linux)](https://rocm.docs.amd.com/en/latest/deploy/linux/quick_start.html).
-
-:::
-
-### Step 2: Download your first model
-Now, let's get your first model:
-
-1. After installation, you'll find the 👋Jan application icon on your desktop. Double-click to open it.
-
-2. Welcome to the Jan homepage. Click on "Explore Models" to see the Model catalog.
-
-![Explore models](/img/explore-model.png)
-
-3. You can also see different quantized versions by clicking on "Show Available Versions."
-
-![Model versions](/img/model-version.png)
-
-> Note: Choose a model that matches your computer's memory and RAM.
-
-4. Select your preferred model and click "Download."
-
-![Downloading](/img/downloading.png)
-
-### Step 3: Start the model
-Once your model is downloaded. Go to "My Models" and then click "Start Model."
-
-![Start model](/img/start-model.png)
-
-
-### Step 4: Start the conversations
-Now you're ready to start using 👋Jan.ai for conversations:
-
-Click "Chat" and begin your first conversation by selecting "New conversation."
-
-You can also check the CPU and Memory usage of the computer.
-
-![Chat](/img/chat.png)
-
-That's it! Enjoy using Large Language Models (LLMs) with 👋Jan.ai.
-
-## Uninstallation
-
-## Troubleshooting
 sudo apt-get remove jan`
 # where jan is the name of Jan package
 ``` 
 In case you wish to completely remove all user data associated with Jan after uninstallation, you can delete the user data folders located at `$HOME/.config/Jan` and ~/.jan. This will return your system to its state prior to the installation of Jan. This method can also be used to reset all settings if you are experiencing any issues with Jan.
diff --git a/docs/docs/install/mac.md b/docs/docs/install/mac.md
@@ -1,84 1,44 @@
 ---
-title: Mac 
 title: Mac
 ---
 
-## Installation
-
-### Step 1: Download the Installer
-To begin using 👋Jan.ai on your Windows computer, follow these steps:
-
-1. Visit [Jan.ai](https://jan.ai/).
-2. Click on the "Download for Windows" button to download the Jan Installer.
-
-![Jan Installer](/img/jan-download.png)
-
-### Step 2: Download your first model
-Now, let's get your first model:
-
-1. After installation, you'll find the 👋Jan application icon on your desktop. Open it.
-
-2. Welcome to the Jan homepage. Click on "Explore Models" to see the Model catalog.
-
-![Explore models](/img/explore-model.png)
-
-3. You can also see different quantized versions by clicking on "Show Available Versions."
-
-![Model versions](/img/model-version.png)
-
-> Note: Choose a model that matches your computer's memory and RAM.
-
-4. Select your preferred model and click "Download."
-
-![Downloading](/img/downloading.png)
-
-### Step 3: Start the model
-Once your model is downloaded. Go to "My Models" and then click "Start Model."
-
-![Start model](/img/start-model.png)
-
-### Step 4: Start the conversations
-Now you're ready to start using 👋Jan.ai for conversations:
-
-Click "Chat" and begin your first conversation by selecting "New conversation."
-
-You can also check the CPU and Memory usage of the computer.
-
-![Chat](/img/chat.png)
-
-That's it! Enjoy using Large Language Models (LLMs) with 👋Jan.ai.
-
-## Uninstallation
-
-As Jan is development mode, you might get stuck on a broken build.
-
-To reset your installation:
 # Jan on MacOS
 
 ## Installation
 1. To download the lastest version of Jan on MacOS, please visit the [Jan's homepage](https://jan.ai/).
 2. On the homepage, please choose the appropriate release version for your system architecture as follows:
  - Intel Mac: `jan-mac-x64-<version>.dmg`
  - Apple Silicon Mac: `jan-mac-arm64-<version>.dmg`
 
 ## Uninstall Jan
 As Jan is development mode, you might get stuck on a broken build
 To reset your installation
 1. Delete Jan from your `/Applications` folder
-
-2. Delete Application data:
- ```sh
- # Newer versions
- rm -rf /Users/$(whoami)/Library/Application\ Support/jan
-
- # Versions 0.2.0 and older
- rm -rf /Users/$(whoami)/Library/Application\ Support/jan-electron
- ```
-
-3. Clear Application cache:
- ```sh
- rm -rf /Users/$(whoami)/Library/Caches/jan*
- ```
-
 2. Delete Application data
 ```bash
 # Newer versions
 rm -rf /Users/$(whoami)/Library/Application\ Support/jan
 
 # Versions 0.2.0 and older
 rm -rf /Users/$(whoami)/Library/Application\ Support/jan-electron
 ```
 3. Clear Application cache
 ```bash
 rm -rf /Users/$(whoami)/Library/Caches/jan*
 ```
 4. Use the following commands to remove any dangling backend processes:
 ```bash
 ps aux | grep nitro
 ```
 Look for processes like "nitro" and "nitro_arm_64," and kill them one by one with:
 ```bash
 kill -9 <PID>
 ```
 
- ```sh
- ps aux | grep nitro
- ```
-
- Look for processes like "nitro" and "nitro_arm_64," and kill them one by one with:
 ## Common Questions
 
- ```sh
- kill -9 <PID>
- ```
 ### Does Jan run on Apple Silicon machines? 
 Yes, Jan supports MacOS Arm64 builds that can run on Macs with the Apple Silicon chipsets. You can install Jan on your Apple Silicon Mac by downloading the `jan-mac-arm64-<version>.dmg` file from the [Jan's homepage](https://jan.ai/).
 
-## FAQs
 ### Which package should I download for my Mac?
 Jan supports both Intel and Apple Silicon Macs. To find which appropriate package to download for your Mac, please follow this official guide from Apple: [Get system information about your Mac - Apple Support](https://support.apple.com/guide/mac-help/syspr35536/mac).
diff --git a/docs/docs/install/overview.md b/docs/docs/install/overview.md
@@ -0,0 1,43 @@
 ---
 title: Overview
 ---
 
 Getting up and running open-source AI models on your own computer with Jan is quick and easy. Jan is lightweight and can run on a variety of hardware and platform versions. Specific requirements tailored to your platform are outlined below.
 
 ## Cross platform
 A free, open-source alternative to OpenAI that runs on the Linux, macOS, and Windows operating systems. Please refer to the specific guides below for your platform
 - [Linux](/install/linux)
 - [MacOS (Mac Intel Chip and Mac Apple Silicon Chip)](/install/mac)
 - [Windows](/install/windows)
 
 ## Requirements for Jan
 
 ### Hardware
 Jan is a lightweight platform designed for seamless download, storage, and execution of open-source Large Language Models (LLMs). With a small download size of less than 200 MB and a disk footprint of under 300 MB, Jan is optimized for efficiency and should run smoothly on modern hardware.
 
 To ensure optimal performance while using Jan and handling LLM models, it is recommended to meet the following system requirements:
 
 #### Disk space
 - Minimum requirement
  - At least 5 GB of free disk space is required to accommodate the download, storage, and management of open-source LLM models.
 - Recommended
  - For an optimal experience and to run most available open-source LLM models on Jan, it is recommended to have 10 GB of free disk space.
 
 #### Random Access Memory (RAM) and Graphics Processing Unit Video Random Access Memory (GPU VRAM)
 The amount of RAM on your system plays a crucial role in determining the size and complexity of LLM models you can effectively run. Jan can be utilized on traditional computers where RAM is a key resource. For enhanced performance, Jan also supports GPU acceleration, utilizing the VRAM of your graphics card. 
 
 #### Relationship between RAM and VRAM Sizes in Relation to LLM Models
 The RAM and GPU VRAM requirements are dependent on the size and complexity of the LLM models you intend to run. The following are some general guidelines to help you determine the amount of RAM or VRAM you need to run LLM models on Jan
 - 8 GB of RAM: Suitable for running smaller models like 3B models or quantized 7B models
 - 16 GB of RAM(recommended): This is considered the "minimum usable models" threshold, particularly for 7B models (e.g Mistral 7B, etc)
 - Beyond 16GB of RAM: Required for handling larger and more sophisticated model, such as 70B models.
 
 ### Architecture 
 Jan is designed to run on muptiple architectures, versatility and widespread usability. The supported architectures include:
 #### CPU
 - x86: Jan is well-suited for systems with x86 architecture, which is commonly found in traditional desktops and laptops. It ensures smooth performance on a variety of devices using x86 processors.
 - ARM: Jan is optimized to run efficiently on ARM-based systems, extending compatibility to a broad range of devices using ARM processors.
 #### GPU
 - NVIDIA: Jan optimizes the computational capabilities of NVIDIA GPUs, achieving efficiency through the utilization of llama.cpp. This strategic integration enhances the performance of Jan, particularly in resource-intensive Language Model (LLM) tasks. Users can expect accelerated processing and improved responsiveness when leveraging the processing capabilities inherent in NVIDIA GPUs.
 - AMD: Users with AMD GPUs can seamlessly integrate Jan's GPU acceleration, offering a comprehensive solution for diverse hardware configurations and preferences.
 - ARM64 Mac: Jan seamlessly supports ARM64 architecture on Mac systems, leveraging Metal for efficient GPU operations. This ensures a smooth and efficient experience for users with Apple Silicon Chips, utilizing the power of Metal for optimal performance on ARM64 Mac devices.