# Khoj 🦅
[](https://github.com/debanjum/khoj/actions/workflows/test.yml)
[](https://github.com/debanjum/khoj/pkgs/container/khoj)
[](https://pypi.org/project/khoj-assistant/)
*A natural language search engine for your personal notes, transactions and images*
**Supported Plugins**
[](https://github.com/debanjum/khoj/tree/master/src/interface/obsidian#readme)
[](https://github.com/debanjum/khoj/tree/master/src/interface/emacs#readme)
## Table of Contents
- [Features](#Features)
- [Demos](#Demos)
- [Khoj in Obsidian](#khoj-in-obsidian)
- [Khoj in Emacs, Browser](#khoj-in-emacs-browser)
- [Interfaces](#Interfaces)
- [Architecture](#Architecture)
- [Setup](#Setup)
- [Install](#1-Install)
- [Configure](#2-Configure)
- [Run](#3-Run)
- [Use](#Use)
- [Interfaces](#Interfaces-1)
- [Query Filters](#Query-filters)
- [Upgrade](#Upgrade)
- [Khoj Server](#upgrade-khoj-server)
- [Khoj.el](#upgrade-khoj-on-emacs)
- [Khoj Obsidian](#upgrade-khoj-on-obsidian)
- [Uninstall Khoj](#uninstall-khoj)
- [Troubleshoot](#Troubleshoot)
- [Advanced Usage](#advanced-usage)
- [Access Khoj on Mobile](#access-khoj-on-mobile)
- [Chat with Notes](#chat-with-notes)
- [Use OpenAI Models for Search](#use-openai-models-for-search)
- [Search across Different Languages](#search-across-different-languages)
- [Miscellaneous](#Miscellaneous)
- [Setup OpenAI API key in Khoj](#set-your-openai-api-key-in-khoj)
- [Beta API](#beta-api)
- [Performance](#Performance)
- [Query Performance](#Query-performance)
- [Indexing Performance](#Indexing-performance)
- [Miscellaneous](#Miscellaneous-1)
- [Development](#Development)
- [Visualize Codebase](#visualize-codebase)
- [Setup](#Setup)
- [Using Pip](#Using-Pip)
- [Using Docker](#Using-Docker)
- [Using Conda](#Using-Conda)
- [Validate](#Validate)
- [Credits](#Credits)
## Features
- **Natural**: Advanced natural language understanding using Transformer based ML Models
- **Local**: Your personal data stays local. All search, indexing is done on your machine[\*](https://github.com/debanjum/khoj#beta-api)
- **Incremental**: Incremental search for a fast, search-as-you-type experience
- **Pluggable**: Modular architecture makes it easy to plug in new data sources, frontends and ML models
- **Multiple Sources**: Search your Org-mode and Markdown notes, Beancount transactions and Photos
- **Multiple Interfaces**: Search from your [Web Browser](./src/khoj/interface/web/index.html), [Emacs](./src/interface/emacs/khoj.el) or [Obsidian](./src/interface/obsidian/)
## Demos
### Khoj in Obsidian
https://user-images.githubusercontent.com/6413477/210486007-36ee3407-e6aa-4185-8a26-b0bfc0a4344f.mp4
Description
- Install Khoj via `pip` and start Khoj backend in non-gui mode
- Install Khoj plugin via Community Plugins settings pane on Obsidian app
- Check the new Khoj plugin settings
- Let Khoj backend index the markdown files in the current Vault
- Open Khoj plugin on Obsidian via Search button on Left Pane
- Search \"*Announce plugin to folks*\" in the [Obsidian Plugin docs](https://marcus.se.net/obsidian-plugin-docs/)
- Jump to the [search result](https://marcus.se.net/obsidian-plugin-docs/publishing/submit-your-plugin)
Description
- Install Khoj via pip
- Start Khoj app
- Add this readme and [khoj.el readme](https://github.com/debanjum/khoj/tree/master/src/interface/emacs) as org-mode for Khoj to index
- Search \"*Setup editor*\" on the Web and Emacs. Re-rank the results for better accuracy
- Top result is what we are looking for, the [section to Install Khoj.el on Emacs](https://github.com/debanjum/khoj/tree/master/src/interface/emacs#2-Install-Khojel)
Analysis
- The results do not have any words used in the query
- *Based on the top result it seems the re-ranking model understands that Emacs is an editor?*
- The results incrementally update as the query is entered
- The results are re-ranked, for better accuracy, once user hits enter
Its simpler as it can skip the configure step below.
### 1. Install
```shell
pip install khoj-assistant
```
### 2. Start App
```shell
khoj
```
### 3. Configure
1. Enable content types and point to files to search in the First Run Screen that pops up on app start
2. Click `Configure` and wait. The app will download ML models and index the content for search
## Use
### Interfaces
- **Khoj via Obsidian**
- [Install](https://github.com/debanjum/khoj/tree/master/src/interface/obsidian#2-Setup-Plugin) the Khoj Obsidian plugin
- Click the *Khoj search* icon 🔎 on the [Ribbon](https://help.obsidian.md/User+interface/Workspace/Ribbon) or Search for *Khoj: Search* in the [Command Palette](https://help.obsidian.md/Plugins/Command+palette)
- **Khoj via Emacs**
- [Install](https://github.com/debanjum/khoj/tree/master/src/interface/emacs#installation) [khoj.el](./src/interface/emacs/khoj.el)
- Run `M-x khoj `
- **Khoj via Web**
- Open via desktop interface or directly
- **Khoj via API**
- See the Khoj FastAPI [Swagger Docs](http://localhost:8000/docs), [ReDocs](http://localhost:8000/redocs)
### Query Filters
Use structured query syntax to filter the natural language search results
- **Word Filter**: Get entries that include/exclude a specified term
- Entries that contain term_to_include: `+"term_to_include"`
- Entries that contain term_to_exclude: `-"term_to_exclude"`
- **Date Filter**: Get entries containing dates in YYYY-MM-DD format from specified date (range)
- Entries from April 1st 1984: `dt:"1984-04-01"`
- Entries after March 31st 1984: `dt>="1984-04-01"`
- Entries before April 2nd 1984 : `dt<="1984-04-01"`
- **File Filter**: Get entries from a specified file
- Entries from incoming.org file: `file:"incoming.org"`
- Combined Example
- `what is the meaning of life? file:"1984.org" dt>="1984-01-01" dt<="1985-01-01" -"big" -"brother"`
- Adds all filters to the natural language query. It should return entries
- from the file *1984.org*
- containing dates from the year *1984*
- excluding words *"big"* and *"brother"*
- that best match the natural language query *"what is the meaning of life?"*
## Upgrade
### Upgrade Khoj Server
```shell
pip install --upgrade khoj-assistant
```
- Note: To upgrade to the latest pre-release version of the khoj server run below command
```shell
# Maps to the latest commit on the master branch
pip install --upgrade --pre khoj-assistant
```
### Upgrade Khoj on Emacs
- Use your Emacs Package Manager to Upgrade
- See [khoj.el readme](https://github.com/debanjum/khoj/tree/master/src/interface/emacs#Upgrade) for details
### Upgrade Khoj on Obsidian
- Upgrade via the Community plugins tab on the settings pane in the Obsidian app
- See the [khoj plugin readme](https://github.com/debanjum/khoj/tree/master/src/interface/obsidian#2-Setup-Plugin) for details
## Uninstall Khoj
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\\.khoj` on Windows)
3. Uninstall the khoj server with `pip uninstall khoj-assistant`
4. (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:
```shell
brew install rustup
rustup-init
source ~/.cargo/env
```
- **Refer**: [Issue with Fix](https://github.com/debanjum/khoj/issues/82#issuecomment-1241890946) for more details
#### Search starts giving wonky results
- **Fix**: Open [/api/update?force=true](http://localhost:8000/api/update?force=true)[^2] in browser to regenerate index from scratch
- **Note**: *This is a fix for when you percieve 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
- **Fix**: Increase RAM available to Docker Containers in Docker Settings
- **Refer**: [StackOverflow Solution](https://stackoverflow.com/a/50770267), [Configure Resources on Docker for Mac](https://docs.docker.com/desktop/mac/#resources)
#### Khoj errors out complaining about Tensors mismatch or null
- **Mitigation**: Disable `image` search using the desktop GUI
## Advanced Usage
### Access Khoj on Mobile
1. [Setup Khoj](#Setup) on your personal server. This can be any always-on machine, i.e an old computer, RaspberryPi(?) etc
2. [Install](https://tailscale.com/kb/installation/) [Tailscale](tailscale.com/) on your personal server and phone
3. Open the Khoj web interface of the server from your phone browser.
It should be `http://tailscale-ip-of-server:8000` or `http://name-of-server:8000` if you've setup [MagicDNS](https://tailscale.com/kb/1081/magicdns/)
4. Click the [Add to Homescreen](https://developer.mozilla.org/en-US/docs/Web/Progressive_web_apps/Add_to_home_screen) button
5. Enjoy exploring your notes, transactions and images from your phone!
### Chat with Notes
#### Overview
- Provides a chat interface to inquire and engage with your notes
- Chat Types:
- **Summarize**: Pulls the most relevant note from your notes and summarizes it
- **Chat**: Also does general chat. It guesses whether to give a general response or search, summarizes from your note.
E.g *"how was your day?"* will give a general response. But *When did I go surfing?* should give a response from your notes
- **Note**: *Your query and top note from search result will be sent to OpenAI for processing*
#### Use
1. [Setup your OpenAI API key in Khoj](#set-your-openai-api-key-in-khoj)
2. Open [/chat?t=summarize](http://localhost:8000/chat?t=summarize)[^2]
3. Type your queries, see summarized response by Khoj from your notes
#### Demo
### Use OpenAI Models for Search
#### Setup
1. Set `encoder-type`, `encoder` and `model-directory` under `asymmetric` and/or `symmetric` `search-type` in your `khoj.yml`[^1]:
```diff
asymmetric:
- encoder: "sentence-transformers/multi-qa-MiniLM-L6-cos-v1"
+ encoder: text-embedding-ada-002
+ encoder-type: src.khoj.utils.models.OpenAI
cross-encoder: "cross-encoder/ms-marco-MiniLM-L-6-v2"
- encoder-type: sentence_transformers.SentenceTransformer
- model_directory: "~/.khoj/search/asymmetric/"
+ model-directory: null
```
2. [Setup your OpenAI API key in Khoj](#set-your-openai-api-key-in-khoj)
3. Restart Khoj server to generate embeddings. It will take longer than with offline models.
#### Warnings
This configuration *uses an online model*
- It will **send all notes to OpenAI** to generate embeddings
- **All queries will be sent to OpenAI** when you search with Khoj
- You will be **charged by OpenAI** based on the total tokens processed
- It *requires an active internet connection* to search and index
### Search across Different Languages
To search for notes in multiple, different languages, you can use a [multi-lingual model](https://www.sbert.net/docs/pretrained_models.html#multi-lingual-models).
For example, the [paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2) supports [50+ languages](https://www.sbert.net/docs/pretrained_models.html#:~:text=we%20used%20the%20following%2050%2B%20languages), has good search quality and speed. To use it:
1. Manually update `search-type > asymmetric > encoder` to `sentence-transformer/paraphrase-multilingual-MiniLM-L12-v2` in your `~/.khoj/khoj.yml` file for now. See diff of `khoj.yml` below for illustration:
```diff
asymmetric:
- encoder: "sentence-transformers/multi-qa-MiniLM-L6-cos-vi"
+ encoder: "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2"
cross-encoder: "cross-encoder/ms-marco-MiniLM-L-6-v2"
model_directory: "~/.khoj/search/asymmetric/"
```
2. Regenerate your content index. For example, by opening [\/api/update?t=force](http://localhost:8000/api/update?t=force)
## Miscellaneous
### Set your OpenAI API key in Khoj
If you want, Khoj can be configured to use OpenAI for search and chat.
Add your OpenAI API to Khoj by using either of the two options below:
- Open the Khoj desktop GUI, add your [OpenAI API key](https://beta.openai.com/account/api-keys) and click *Configure*
Ensure khoj is started without the `--no-gui` flag. Check your system tray to see if Khoj 🦅 is minimized there.
- Set `openai-api-key` field under `processor.conversation` section in your `khoj.yml`[^1] to your [OpenAI API key](https://beta.openai.com/account/api-keys) and restart khoj:
```diff
processor:
conversation:
- openai-api-key: # "YOUR_OPENAI_API_KEY"
+ openai-api-key: sk-aaaaaaaaaaaaaaaaaaaaaaaahhhhhhhhhhhhhhhhhhhhhhhh
model: "text-davinci-003"
conversation-logfile: "~/.khoj/processor/conversation/conversation_logs.json"
```
**Warning**: *This will enable khoj to send your query and note(s) to OpenAI for processing*
### Beta API
- The beta [chat](http://localhost:8000/api/beta/chat), [summarize](http://localhost:8000/api/beta/summarize) and [search](http://localhost:8000/api/beta/search) API endpoints use [OpenAI API](https://openai.com/api/)
- They are disabled by default
- To use them:
1. [Setup your OpenAI API key in Khoj](#set-your-openai-api-key-in-khoj)
2. Interact with them from the [Khoj Swagger docs](http://locahost:8000/docs)[^2]
## Performance
### Query performance
- Semantic search using the bi-encoder is fairly fast at \<50 ms
- Reranking using the cross-encoder is slower at \<2s on 15 results. Tweak `top_k` to tradeoff speed for accuracy of results
- Filters in query (e.g by file, word or date) usually add \<20ms to query latency
### Indexing performance
- Indexing is more strongly impacted by the size of the source data
- Indexing 100K+ line corpus of notes takes about 10 minutes
- Indexing 4000+ images takes about 15 minutes and more than 8Gb of RAM
- Note: *It should only take this long on the first run* as the index is incrementally updated
### Miscellaneous
- Testing done on a Mac M1 and a \>100K line corpus of notes
- Search, indexing on a GPU has not been tested yet
## Development
### Visualize Codebase
*[Interactive Visualization](https://mango-dune-07a8b7110.1.azurestaticapps.net/?repo=debanjum%2Fkhoj)*
### Setup
#### Using Pip
##### 1. Install
```shell
git clone https://github.com/debanjum/khoj && cd khoj
python3 -m venv .venv && source .venv/bin/activate
pip install -e .[dev]
```
##### 2. Run
1. Start Khoj
```shell
khoj -vv
```
2. Configure Khoj
- **Via GUI**: Add files, directories to index in the GUI window that pops up on starting Khoj, then Click Configure
- **Manually**:
- Copy the `config/khoj_sample.yml` to `~/.khoj/khoj.yml`
- Set `input-files` or `input-filter` in each relevant `content-type` section of `~/.khoj/khoj.yml`
- Set `input-directories` field in `image` `content-type` section
- Delete `content-type` and `processor` sub-section(s) irrelevant for your use-case
- Restart khoj
Note: Wait after configuration for khoj to Load ML model, generate embeddings and expose API to query notes, images, transactions etc specified in config YAML
#### Using Docker
##### 1. Clone
```shell
git clone https://github.com/debanjum/khoj && cd khoj
```
##### 2. Configure
- **Required**: Update [docker-compose.yml](./docker-compose.yml) to mount your images, (org-mode or markdown) notes and beancount directories
- **Optional**: Edit application configuration in [khoj_docker.yml](./config/khoj_docker.yml)
##### 3. Run
```shell
docker-compose up -d
```
*Note: The first run will take time. Let it run, it\'s mostly not hung, just generating embeddings*
##### 4. Upgrade
```shell
docker-compose build --pull
```
#### Using Conda
##### 1. Install Dependencies
- [Install Conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html)
##### 2. Install Khoj
```shell
git clone https://github.com/debanjum/khoj && cd khoj
conda env create -f config/environment.yml
conda activate khoj
python3 -m pip install pyqt6 # As conda does not support pyqt6 yet
```
##### 3. Configure
- Copy the `config/khoj_sample.yml` to `~/.khoj/khoj.yml`
- Set `input-files` or `input-filter` in each relevant `content-type` section of `~/.khoj/khoj.yml`
- Set `input-directories` field in `image` `content-type` section
- Delete `content-type`, `processor` sub-sections irrelevant for your use-case
##### 4. Run
```shell
python3 -m src.khoj.main -vv
```
Load ML model, generate embeddings and expose API to query notes, images, transactions etc specified in config YAML
##### 5. Upgrade
```shell
cd khoj
git pull origin master
conda deactivate khoj
conda env update -f config/environment.yml
conda activate khoj
```
### Validate
#### Before Make Changes
1. Install Git Hooks for Validation
```shell
pre-commit install -t pre-push -t pre-commit
```
- This ensures standard code formatting fixes and other checks run automatically on every commit and push
- Note 1: If [pre-commit](https://pre-commit.com/#intro) didn't already get installed, [install it](https://pre-commit.com/#install) via `pip install pre-commit`
- Note 2: To run the pre-commit changes manually, use `pre-commit run --hook-stage manual --all` before creating PR
#### Before Creating PR
1. Run Tests
```shell
pytest
```
2. Run MyPy to check types
```shell
mypy --config-file pyproject.toml
```
#### After Creating PR
- Automated [validation workflows](.github/workflows) run for every PR.
Ensure any issues seen by them our fixed
- Test the python packge created for a PR
1. Download and extract the zipped `.whl` artifact generated from the pypi workflow run for the PR.
2. Install (in your virtualenv) with `pip install /path/to/download*.whl>`
3. Start and use the application to see if it works fine
## Credits
- [Multi-QA MiniLM Model](https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1), [All MiniLM Model](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) for Text Search. See [SBert Documentation](https://www.sbert.net/examples/applications/retrieve_rerank/README.html)
- [OpenAI CLIP Model](https://github.com/openai/CLIP) for Image Search. See [SBert Documentation](https://www.sbert.net/examples/applications/image-search/README.html)
- Charles Cave for [OrgNode Parser](http://members.optusnet.com.au/~charles57/GTD/orgnode.html)
- [Org.js](https://mooz.github.io/org-js/) to render Org-mode results on the Web interface
- [Markdown-it](https://github.com/markdown-it/markdown-it) to render Markdown results on the Web interface
[^1]: Default Khoj config file @ `~/.khoj/khoj.yml`
[^2]: Default Khoj url @ http://localhost:8000