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Self-Host

documentation/docs/get-started/setup.mdx

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Self-Host

Learn about how to self-host Khoj on your own machine.

Benefits to self-hosting:

  1. Privacy: Your data will never have to leave your private network. You can even use Khoj without an internet connection if deployed on your personal computer.
  2. Customization: You can customize Khoj to your liking, from models, to host URL, to feature enablement.
mdx-code-block
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';

Setup Khoj

These are the general setup instructions for self-hosted Khoj. You can install the Khoj server using either Docker or Pip.

:::info[First Run] Restart your Khoj server after the first run to ensure all settings are applied correctly. :::

<Tabs groupId="server" queryString> <TabItem value="docker" label="Docker"> <Tabs groupId="operating-systems" queryString="os"> <TabItem value="macos" label="MacOS"> <h3>Prerequisites</h3> <h4>Docker</h4> - *Option 1*: Click here to install [Docker Desktop](https://docs.docker.com/desktop/install/mac-install/). Make sure you also install the [Docker Compose](https://docs.docker.com/desktop/install/mac-install/) tool.
    - *Option 2*: Use [Homebrew](https://brew.sh/) to install Docker and Docker Compose.
      ```shell
      brew install --cask docker
      brew install docker-compose
      ```
    <h3>Setup</h3>
    1. Download the Khoj docker-compose.yml file [from Github](https://github.com/khoj-ai/khoj/blob/master/docker-compose.yml)
       ```shell
       mkdir ~/.khoj && cd ~/.khoj
       wget https://raw.githubusercontent.com/khoj-ai/khoj/master/docker-compose.yml
       ```
    2. Configure the environment variables in the `docker-compose.yml`
       - Set `KHOJ_ADMIN_PASSWORD`, `KHOJ_DJANGO_SECRET_KEY` (and optionally the `KHOJ_ADMIN_EMAIL`) to something secure. This allows you to customize Khoj later via the admin panel.
       - Set `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, or `GEMINI_API_KEY` to your API key if you want to use OpenAI, Anthropic or Gemini commercial chat models respectively.
       - Uncomment `OPENAI_BASE_URL` to use [Ollama](/advanced/ollama?type=first-run&server=docker#setup) running on your host machine. Or set it to the URL of your OpenAI compatible API like vLLM or [LMStudio](/advanced/lmstudio).
    3. Start Khoj by running the following command in the same directory as your docker-compose.yml file.
       ```shell
       cd ~/.khoj
       docker-compose up
       ```
  </TabItem>
  <TabItem value="windows" label="Windows">
  <h3>Prerequisites</h3>
  1. Install [WSL2](https://learn.microsoft.com/en-us/windows/wsl/install) and restart your machine
     ```shell
     # Run in PowerShell
     wsl --install
     ```
  2. Install [Docker Desktop](https://docs.docker.com/desktop/install/windows-install/) with **[WSL2 backend](https://docs.docker.com/desktop/wsl/#turn-on-docker-desktop-wsl-2)** (default)

  <h3>Setup</h3>
  1. Download the Khoj docker-compose.yml file [from Github](https://github.com/khoj-ai/khoj/blob/master/docker-compose.yml)
     ```shell
     # Windows users should use their WSL2 terminal to run these commands
     mkdir ~/.khoj && cd ~/.khoj
     wget https://raw.githubusercontent.com/khoj-ai/khoj/master/docker-compose.yml
     ```
  2. Configure the environment variables in the `docker-compose.yml`
     - Set `KHOJ_ADMIN_PASSWORD`, `KHOJ_DJANGO_SECRET_KEY` (and optionally the `KHOJ_ADMIN_EMAIL`) to something secure. This allows you to customize Khoj later via the admin panel.
     - Set `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, or `GEMINI_API_KEY` to your API key if you want to use OpenAI, Anthropic or Gemini commercial chat models respectively.
     - Uncomment `OPENAI_BASE_URL` to use [Ollama](/advanced/ollama) running on your host machine. Or set it to the URL of your OpenAI compatible API like vLLM or [LMStudio](/advanced/lmstudio).
  3. Start Khoj by running the following command in the same directory as your docker-compose.yml file.
     ```shell
     # Windows users should use their WSL2 terminal to run these commands
     cd ~/.khoj
     docker-compose up
     ```
  </TabItem>
  <TabItem value="linux" label="Linux">
    <h3>Prerequisites</h3>
    Install [Docker Desktop](https://docs.docker.com/desktop/install/linux/).
    You can also use your package manager to install Docker Engine & Docker Compose.

    <h3>Setup</h3>
    1. Download the Khoj docker-compose.yml file [from Github](https://github.com/khoj-ai/khoj/blob/master/docker-compose.yml)
       ```shell
       mkdir ~/.khoj && cd ~/.khoj
       wget https://raw.githubusercontent.com/khoj-ai/khoj/master/docker-compose.yml
       ```
    2. Configure the environment variables in the `docker-compose.yml`
       - Set `KHOJ_ADMIN_PASSWORD`, `KHOJ_DJANGO_SECRET_KEY` (and optionally the `KHOJ_ADMIN_EMAIL`) to something secure. This allows you to customize Khoj later via the admin panel.
       - Set `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, or `GEMINI_API_KEY` to your API key if you want to use OpenAI, Anthropic or Gemini commercial chat models respectively.
       - Uncomment `OPENAI_BASE_URL` to use [Ollama](/advanced/ollama) running on your host machine. Or set it to the URL of your OpenAI compatible API like vLLM or [LMStudio](/advanced/lmstudio).
    3. Start Khoj by running the following command in the same directory as your docker-compose.yml file.
       ```shell
       cd ~/.khoj
       docker-compose up
       ```
  </TabItem>
</Tabs>

:::info[Remote Access] By default Khoj is only accessible on the machine it is running. To access Khoj from a remote machine see Remote Access Docs. :::

Your setup is complete once you see 🌖 Khoj is ready to engage in the server logs on your terminal. </TabItem> <TabItem value="pip" label="Pip">

<h3>1. Install Khoj Server</h3> - Make sure [python](https://realpython.com/installing-python/) and [pip](https://pip.pypa.io/en/stable/installation/) are installed on your machine - Check [llama-cpp-python setup](https://github.com/abetlen/llama-cpp-python?tab=readme-ov-file#supported-backends) if you hit any llama-cpp issues with the installation

Run the following command in your terminal to install the Khoj server.

<Tabs groupId="operating-systems" queryString="os"> <TabItem value="macos" label="MacOS"> <Tabs groupId="gpu" queryString="gpu"> <TabItem value="arm" label="ARM/M1+"> ```shell CMAKE_ARGS="-DGGML_METAL=on" python -m pip install 'khoj[local]' ``` </TabItem> <TabItem value="intel" label="Intel"> ```shell python -m pip install 'khoj[local]' ``` </TabItem> </Tabs> </TabItem> <TabItem value="windows" label="Windows"> Run the following command in PowerShell on Windows <Tabs groupId="gpu" queryString="gpu"> <TabItem value="cpu" label="CPU"> ```shell # Install Khoj py -m pip install 'khoj[local]' ``` </TabItem> <TabItem value="nvidia" label="NVIDIA (CUDA) GPU"> ```shell # 1. To use NVIDIA (CUDA) GPU $env:CMAKE_ARGS = "-DGGML_CUDA=on" # 2. Install Khoj py -m pip install 'khoj[local]' ``` </TabItem> <TabItem value="amd" label="AMD (ROCm) GPU"> ```shell # 1. To use AMD (ROCm) GPU $env:CMAKE_ARGS = "-DGGML_HIPBLAS=on" # 2. Install Khoj py -m pip install 'khoj[local]' ``` </TabItem> <TabItem value="vulkan" label="VULKAN GPU"> ```shell # 1. To use VULCAN GPU $env:CMAKE_ARGS = "-DGGML_VULKAN=on" # 2. Install Khoj py -m pip install 'khoj[local]' ``` </TabItem> </Tabs> </TabItem> <TabItem value="linux" label="Linux"> <Tabs groupId="gpu" queryString="gpu"> <TabItem value="cpu" label="CPU"> ```shell python -m pip install 'khoj[local]' ``` </TabItem> <TabItem value="nvidia" label="NVIDIA (CUDA) GPU"> ```shell CMAKE_ARGS="-DGGML_CUDA=on" FORCE_CMAKE=1 python -m pip install 'khoj[local]' ``` </TabItem> <TabItem value="amd" label="AMD (ROCm) GPU"> ```shell CMAKE_ARGS="-DGGML_HIPBLAS=on" FORCE_CMAKE=1 python -m pip install 'khoj[local]' ``` </TabItem> <TabItem value="vulkan" label="VULKAN GPU"> ```shell CMAKE_ARGS="-DGGML_VULKAN=on" FORCE_CMAKE=1 python -m pip install 'khoj[local]' ``` </TabItem> </Tabs> </TabItem> </Tabs> <h3>2. Start Khoj Server</h3>

Run the following command from your terminal to start the Khoj service.

shell
USE_EMBEDDED_DB="true" khoj --anonymous-mode

--anonymous-mode allows access to Khoj without requiring login. This is usually fine for local only, single user setups. If you need authentication follow the authentication setup docs.

<h4>First Run</h4> On the first run of the above command, you will be prompted to: 1. Create an admin account with an email and secure password 2. Customize the chat models to enable - Keep your [OpenAI](https://platform.openai.com/api-keys), [Anthropic](https://console.anthropic.com/account/keys), [Gemini](https://aistudio.google.com/app/apikey) API keys and [OpenAI](https://platform.openai.com/docs/models), [Anthropic](https://docs.anthropic.com/en/docs/about-claude/models#model-names), [Gemini](https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-models), [Offline](https://huggingface.co/models?pipeline_tag=text-generation&library=gguf) chat model names handy to set any of them up during first run. 3. Your setup is complete once you see `🌖 Khoj is ready to engage` in the server logs on your terminal!

:::tip[Auto Start] To start Khoj automatically in the background use Task scheduler on Windows or Cron on Mac, Linux (e.g. with @reboot khoj) ::: </TabItem> </Tabs>

Use Khoj

You can now open the web app at http://localhost:42110 and start interacting!

Nothing else is necessary, but you can customize your setup further by following the steps below.

Add Chat Models

<h4>Login to the Khoj Admin Panel</h4> Go to http://localhost:42110/server/admin and login with the admin credentials you setup during installation.

:::info[CSRF Error] Ensure you are using localhost, not 127.0.0.1, to access the admin panel to avoid the CSRF error. :::

:::info[CSRF Trusted Origin or Unset Cookie Error] If using a load balancer/reverse_proxy in front of your Khoj server: Set the environment variable KHOJ_ALLOWED_DOMAIN=your-internal-ip-or-domain to avoid this error. If unset, it defaults to KHOJ_DOMAIN. :::

:::info[DISALLOWED HOST or Bad Request (400) Error] You may hit this if you try access Khoj exposed on a custom domain (e.g. 192.168.12.3 or example.com) or over HTTP. Set the environment variables KHOJ_DOMAIN=your-external-ip-or-domain and KHOJ_NO_HTTPS=True if required to avoid this error. :::

:::tip[Note] Using Safari on Mac? You might not be able to login to the admin panel. Try using Chrome or Firefox instead. :::

<h4>Configure Chat Model</h4> Setup which chat model you'd want to use. Khoj supports local and online chat models. <Tabs groupId="chatmodel" queryString> <TabItem value="openai" label="OpenAI">

:::info[Ollama Integration] Using Ollama? See the Ollama Integration section for more custom setup instructions. :::

  1. Create a new AI Model Api in the server admin settings.
    • Add your OpenAI API key
    • Give the configuration a friendly name like OpenAI
    • (Optional) Set the API base URL. It is only relevant if you're using another OpenAI-compatible proxy server like Ollama or LMStudio.

2. Create a new chat model - Set the chat-model field to an OpenAI chat model. Example: gpt-4o. - Make sure to set the model-type field to OpenAI. - If your model supports vision, set the vision enabled field to true. This is currently only supported for OpenAI models with vision capabilities. - The tokenizer and max-prompt-size fields are optional. Set them only if you're sure of the tokenizer or token limit for the model you're using. Contact us if you're unsure what to do here.

</TabItem> <TabItem value="anthropic" label="Anthropic">

  1. Create a new AI Model API in the server admin settings.
    • Add your Anthropic API key
    • Give the configuration a friendly name like Anthropic. Do not configure the API base url.
  2. Create a new chat model
    • Set the chat-model field to an Anthropic chat model. Example: claude-3-5-sonnet-20240620.
    • Set the model-type field to Anthropic.
    • Set the ai model api field to the Anthropic AI Model API you created in step 1. </TabItem>
<TabItem value="gemini" label="Gemini"> 1. Create a new [AI Model API](http://localhost:42110/server/admin/database/aimodelapi/add) in the server admin settings. - Add your [Gemini API key](https://aistudio.google.com/app/apikey) - Give the configuration a friendly name like `Gemini`. Do not configure the API base url. 2. Create a new [chat model](http://localhost:42110/server/admin/database/chatmodel/add) - Set the `chat-model` field to a [Google Gemini chat model](https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-models). Example: `gemini-2.5-flash`. - Set the `model-type` field to `Google`. - Set the `ai model api` field to the Gemini AI Model API you created in step 1. </TabItem> <TabItem value="offline" label="Offline"> Offline chat stays completely private and can work without internet using any open-weights model.

:::tip[System Requirements]

  • Minimum 8 GB RAM. Recommend 16Gb VRAM
  • Minimum 5 GB of Disk available
  • A Nvidia, AMD GPU or a Mac M1+ machine would significantly speed up chat responses :::
  1. Install any Openai API compatible local ai model server like llama-cpp-server, Ollama, vLLM etc.
  2. Add an ai model api on the admin panel
    • Set the api url field to the url of your local ai model provider like http://localhost:11434/v1/ for Ollama
  3. Restart the Khoj server to load models available on your local ai model provider
    • If that doesn't work, you'll need to manually add available chat model in the admin panel.
  4. Set the newly added chat model as your preferred model in your User chat settings
  5. Start chatting with your local AI! </TabItem>
</Tabs>

:::tip[Multiple Chat Models] Set your preferred default chat model in the Default, Advanced fields of your ServerChatSettings. Khoj uses these chat model for all intermediate steps like intent detection, web search etc. :::

:::info[Chat Model Fields]

  • The tokenizer and max-prompt-size fields are optional. Set them only if you're sure of the tokenizer or token limit for the model you're using. This improves context stuffing. Contact us if you're unsure what to do here.
  • Only tick the vision enabled field for OpenAI models with vision capabilities like gpt-4o. Vision capabilities in other chat models is not currently utilized. :::

Sync your Knowledge

  • You can chat with your notes and documents using Khoj.
  • Khoj can keep your files and folders synced using the Khoj Desktop, Obsidian or Emacs clients.
  • Your Notion workspace can be directly synced from the web app.
  • You can also just drag and drop specific files you want to chat with on the Web app.

Setup Khoj Clients

The Khoj web app is available by default to chat, search and configure Khoj.

You can also install a Khoj client to easily access it from Obsidian, Emacs, Whatsapp or your OS and keep your documents synced with Khoj.

:::info[Note] Set the host URL on your clients settings page to your Khoj server URL. By default, use http://127.0.0.1:42110 or http://localhost:42110. Note that localhost may not work in all cases. :::

<Tabs groupId="client" queryString> <TabItem value="desktop" label="Desktop"> - Read the Khoj Desktop app [setup docs](/clients/desktop#setup). </TabItem> <TabItem value="emacs" label="Emacs"> - Read the Khoj Emacs package [setup docs](/clients/emacs#setup). </TabItem> <TabItem value="obsidian" label="Obsidian"> - Read the Khoj Obsidian plugin [setup docs](/clients/obsidian#setup). </TabItem> <TabItem value="whatsapp" label="Whatsapp"> - Read the Khoj Whatsapp app [setup docs](/clients/whatsapp). </TabItem> </Tabs>

Upgrade

Upgrade Server

<Tabs groupId="server" queryString> <TabItem value="pip" label="Pip"> ```shell pip install --upgrade khoj ``` *Note: To upgrade to the latest pre-release version of the khoj server run below command* </TabItem> <TabItem value="docker" label="Docker"> Run the commands below from the same directory where you have your `docker-compose.yml` file. This will fetch the latest build and upgrade your server. ```shell # Windows users should use their WSL2 terminal to run these commands cd ~/.khoj # assuming your khoj docker-compose.yml file is here docker-compose up --build ``` </TabItem> </Tabs>

Upgrade Clients

<Tabs groupId="client" queryString> <TabItem value="desktop" label="Desktop"> - The Desktop app automatically updates to the latest released version on restart. - You can manually download the latest version from the [Khoj Website](https://khoj.dev/downloads). </TabItem> <TabItem value="emacs" label="Emacs"> - Use your Emacs Package Manager to Upgrade - See [khoj.el package setup](/clients/emacs#setup) for details </TabItem> <TabItem value="obsidian" label="Obsidian"> - Upgrade via the Community plugins tab on the settings pane in the Obsidian app - See the [khoj plugin setup](/clients/obsidian#setup) for details </TabItem> </Tabs>

Uninstall

Uninstall Server

<Tabs groupId="server" queryString> <TabItem value="pip" label="Pip"> ```shell # uninstall khoj server pip uninstall khoj
# delete khoj postgres db
dropdb khoj -U postgres
```
</TabItem>
<TabItem value="docker" label="Docker">
Run the command below from the same directory where you have your `docker-compose` file.
This will remove the server containers, networks, images and volumes.

```shell
docker-compose down --volumes
```
</TabItem>
</Tabs>

Uninstall Clients

<Tabs groupId="client" queryString> <TabItem value="desktop" label="Desktop"> Uninstall the Khoj Desktop client in the standard way from your OS. </TabItem> <TabItem value="emacs" label="Emacs"> Uninstall the Khoj Emacs package in the standard way from Emacs. </TabItem> <TabItem value="obsidian" label="Obsidian"> Uninstall via the Community plugins tab on the settings pane in the Obsidian app </TabItem> </Tabs>

Troubleshoot

Dependency conflict when trying to install Khoj python package with pip

  • Reason: When conflicting dependency versions are required by Khoj vs other python packages installed on your system
  • Fix: Install Khoj in a python virtual environment using venv or pipx to avoid this dependency conflicts
  • Process:
    1. Install pipx
    2. Use pipx to install Khoj to avoid dependency conflicts with other python packages.
      shell
      pipx install khoj
      
    3. Now start khoj using the standard steps described earlier

Install fails while building Tokenizer dependency

  • Details: pip install khoj fails while building the tokenizers dependency. Complains about Rust.
  • Fix: Install Rust to build the tokenizers package. For example on Mac run:
    shell
    brew install rustup
    rustup-init
    source ~/.cargo/env
    
  • Refer: Issue with Fix for more details

Khoj in Docker errors out with "Killed" in error message