khoj/docs/setup.md
sabaimran 343854752c
Improve docker builds for local hosting (#476)
* Remove GPT4All dependency in pyproject.toml and use multiplatform builds in the dockerization setup in GH actions
* Move configure_search method into indexer
* Add conditional installation for gpt4all
* Add hint to go to localhost:42110 in the docs. Addresses #477
2023-09-08 17:07:26 -07:00

4.9 KiB

Setup

These are the general setup instructions for Khoj.

  • Make sure python and pip are installed on your machine
  • Check the Khoj Emacs docs to setup Khoj with Emacs
    Its simpler as it can skip the server install, run and configure step below.
  • Check the Khoj Obsidian docs to setup Khoj with Obsidian
    Its simpler as it can skip the configure step below.

1. Install

1.1 Local Setup

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

  • On Linux/MacOS

    python -m pip install khoj-assistant
    
  • On Windows

    py -m pip install khoj-assistant
    

For more detailed Windows installation and troubleshooting, see Windows Install.

1.1.1 Start

Run the following command from your terminal to start the Khoj backend and open Khoj in your browser.

khoj

Khoj should now be running at http://localhost:42110. You can see the web UI in your browser.

Note: To start Khoj automatically in the background use Task scheduler on Windows or Cron on Mac, Linux (e.g with @reboot khoj)

1.2 Docker Setup

Use the sample docker-compose in Github to run Khoj in Docker. To start the container, run the following command in the same directory as the docker-compose.yml file. You'll have to configure the mounted directories to match your local knowledge base.

docker-compose up

Khoj should now be running at http://localhost:42110. You can see the web UI in your browser.

2. Configure

  1. Set File, Folder and hit Save in each Plugins you want to enable for Search on the Khoj config page
  2. Add your OpenAI API key to Chat Feature settings if you want to use Chat
  3. Click Configure and wait. The app will download ML models and index the content for search and (optionally) chat

configure demo

3. Install Interface Plugins (Optional)

Khoj exposes a web interface to search, chat and configure by default.
The optional steps below allow using Khoj from within an existing application like Obsidian or Emacs.

  • Khoj Obsidian:
    Install the Khoj Obsidian plugin

  • Khoj Emacs:
    Install khoj.el

Upgrade

Upgrade Khoj Server

pip install --upgrade khoj-assistant

Note: To upgrade to the latest pre-release version of the khoj server run below command

# Maps to the latest commit on the master branch
pip install --upgrade --pre khoj-assistant

Upgrade Khoj on Emacs

Upgrade Khoj on Obsidian

  • Upgrade via the Community plugins tab on the settings pane in the Obsidian app
  • See the khoj plugin setup for details

Uninstall

  1. (Optional) Hit Ctrl-C in the terminal running the khoj server to stop it
  2. Delete the khoj directory in your home folder (i.e ~/.khoj on Linux, Mac or C:\Users\<your-username>\.khoj on Windows)
  3. You might want to rm -rf the following directories:
  • ~/.khoj
  • ~/.cache/gpt4all
  1. Uninstall the khoj server with pip uninstall khoj-assistant
  2. (Optional) Uninstall khoj.el or the khoj obsidian plugin in the standard way on Emacs, Obsidian

Troubleshoot

Install fails while building Tokenizer dependency

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

Search starts giving wonky results

  • Fix: Open /api/update?force=true in browser to regenerate index from scratch
  • Note: This is a fix for when you perceive the search results have degraded. Not if you think they've always given wonky results

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

Khoj errors out complaining about Tensors mismatch or null

  • Mitigation: Disable image search using the desktop GUI