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# Khoj 🦅
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[![build ](https://github.com/debanjum/khoj/actions/workflows/build.yml/badge.svg )](https://github.com/debanjum/khoj/actions/workflows/build.yml)
[![test ](https://github.com/debanjum/khoj/actions/workflows/test.yml/badge.svg )](https://github.com/debanjum/khoj/actions/workflows/test.yml)
[![publish ](https://github.com/debanjum/khoj/actions/workflows/publish.yml/badge.svg )](https://github.com/debanjum/khoj/actions/workflows/publish.yml)
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*A natural language search engine for your personal notes, transactions and images*
## Table of Contents
- [Features ](#Features )
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- [Demos ](#Demos )
- [Khoj in Obsidian ](#khoj-in-obsidian )
- [Khoj in Emacs, Browser ](#khoj-in-emacs-browser )
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- [Interfaces ](#Interfaces )
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- [Architecture ](#Architecture )
- [Setup ](#Setup )
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- [Install ](#1-Install )
- [Configure ](#2-Configure )
- [Run ](#3-Run )
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- [Use ](#Use )
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- [Interfaces ](#Interfaces-1 )
- [Query Filters ](#Query-filters )
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- [Upgrade ](#Upgrade )
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- [Khoj Server ](#upgrade-khoj-server )
- [Khoj.el ](#upgrade-khoj-on-emacs )
- [Khoj Obsidian ](#upgrade-khoj-on-obsidian )
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- [Troubleshoot ](#Troubleshoot )
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- [Advanced Usage ](#advanced-usage )
- [Access Khoj on Mobile ](#access-khoj-on-mobile )
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- [Miscellaneous ](#Miscellaneous )
- [Performance ](#Performance )
- [Query Performance ](#Query-performance )
- [Indexing Performance ](#Indexing-performance )
- [Miscellaneous ](#Miscellaneous-1 )
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- [Development ](#Development )
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- [Visualize Codebase ](#visualize-codebase )
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- [Setup ](#Setup )
- [Using Pip ](#Using-Pip )
- [Using Docker ](#Using-Docker )
- [Using Conda ](#Test )
- [Test ](#Test )
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- [Credits ](#Credits )
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## Features
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- **Natural**: Advanced natural language understanding using Transformer based ML Models
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- **Local**: Your personal data stays local. All search, indexing is done on your machine[\*](https://github.com/debanjum/khoj#miscellaneous)
- **Incremental**: Incremental search for a fast, search-as-you-type experience
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- **Pluggable**: Modular architecture makes it easy to plug in new data sources, frontends and ML models
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- **Multiple Sources**: Search your Org-mode and Markdown notes, Beancount transactions and Photos
- **Multiple Interfaces**: Search using a [Web Browser ](./src/interface/web/index.html ), [Emacs ](./src/interface/emacs/khoj.el ) or the [API ](http://localhost:8000/docs )
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## Demos
### Khoj in Obsidian
https://user-images.githubusercontent.com/6413477/210486007-36ee3407-e6aa-4185-8a26-b0bfc0a4344f.mp4
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< details > < summary > Description< / summary >
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- 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 )
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< / details >
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### Khoj in Emacs, Browser
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https://user-images.githubusercontent.com/6413477/184735169-92c78bf1-d827-4663-9087-a1ea194b8f4b.mp4
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< details > < summary > Description< / summary >
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- 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
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- 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#installation )
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< / details >
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< details > < summary > Analysis< / summary >
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- The results do not have any words used in the query
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- *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
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- The results are re-ranked, for better accuracy, once user hits enter
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< / details >
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### Interfaces
![](https://github.com/debanjum/khoj/blob/master/docs/interfaces.png)
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## Architecture
![](https://github.com/debanjum/khoj/blob/master/docs/khoj_architecture.png)
## Setup
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These are the general setup instructions for Khoj.
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Check the [Khoj Obsidian Readme ](https://github.com/debanjum/khoj/tree/master/src/interface/obsidian#Setup ) to setup Khoj with the Obsidian Plugin. Its simpler as it can skip the configure step below.
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### 1. Install
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```shell
pip install khoj-assistant
```
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### 2. Start App
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```shell
khoj
```
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### 3. Configure
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1. Enable content types and point to files to search in the First Run Screen that pops up on app start
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2. Click `Configure` and wait. The app will download ML models and index the content for search
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## Use
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### Interfaces
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- **Khoj via Obsidian**
- [Install ](https://github.com/debanjum/khoj/tree/master/src/interface/obsidian#2-Setup-Plugin ) the Khoj Obsidian plugin
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- 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 )
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- **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 <user-query>`
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- **Khoj via Web**
- Open < http: // localhost:8000 /> via desktop interface or directly
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- **Khoj via API**
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- See the Khoj FastAPI [Swagger Docs ](http://localhost:8000/docs ), [ReDocs ](http://localhost:8000/redocs )
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### 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?"*
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## Upgrade
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### Upgrade Khoj Server
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```shell
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pip install --upgrade khoj-assistant
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```
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### 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
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## Troubleshoot
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- Symptom: Errors out complaining about Tensors mismatch, null etc
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- Mitigation: Disable `image` search using the desktop GUI
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- Symptom: Errors out with \"Killed\" in error message in Docker
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- 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 )
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- Symptom: `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
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# 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-url-of-server:8000` or `http://name-of-server:8000` if you've setup [MagicDNS ](https://tailscale.com/kb/1081/magicdns/ )
4. Click the [Install/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!
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![](https://github.com/debanjum/khoj/blob/master/docs/khoj_pwa_android.png)
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## Miscellaneous
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- The beta [chat ](http://localhost:8000/api/beta/chat ) and [search ](http://localhost:8000/api/beta/search ) API endpoints use [OpenAI API ](https://openai.com/api/ )
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- It is disabled by default
- To use it add your `openai-api-key` via the app configure screen
- Warning: *If you use the above beta APIs, your query and top result(s) will be sent to OpenAI for processing*
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## Performance
### Query performance
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- Semantic search using the bi-encoder is fairly fast at \<50 ms
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- Reranking using the cross-encoder is slower at \<2s on 15 results. Tweak `top_k` to tradeoff speed for accuracy of results
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- Filters in query (e.g by file, word or date) usually add \<20ms to query latency
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### Indexing performance
- Indexing is more strongly impacted by the size of the source data
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- Indexing 100K+ line corpus of notes takes about 10 minutes
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- Indexing 4000+ images takes about 15 minutes and more than 8Gb of RAM
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- Note: *It should only take this long on the first run* as the index is incrementally updated
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### Miscellaneous
- Testing done on a Mac M1 and a \>100K line corpus of notes
- Search, indexing on a GPU has not been tested yet
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## Development
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### Visualize Codebase
*[Interactive Visualization](https://mango-dune-07a8b7110.1.azurestaticapps.net/?repo=debanjum%2Fkhoj)*
![](https://github.com/debanjum/khoj/blob/master/docs/khoj_codebase_visualization_0.2.1.png)
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### Setup
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#### Using Pip
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##### 1. Install
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```shell
git clone https://github.com/debanjum/khoj & & cd khoj
python3 -m venv .venv & & source .venv/bin/activate
pip install -e .
```
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##### 2. Configure
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- 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
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##### 3. Run
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```shell
khoj -vv
```
Load ML model, generate embeddings and expose API to query notes, images, transactions etc specified in config YAML
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##### 4. Upgrade
```shell
# To Upgrade To Latest Stable Release
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# Maps to the latest tagged version of khoj on master branch
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pip install --upgrade khoj-assistant
# To Upgrade To Latest Pre-Release
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# Maps to the latest commit on the master branch
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pip install --upgrade --pre khoj-assistant
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# To Upgrade To Specific Development Release.
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# Useful to test, review a PR.
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# Note: khoj-assistant is published to test PyPi on creating a PR
pip install -i https://test.pypi.org/simple/ khoj-assistant==0.1.5.dev57166025766
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```
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#### Using Docker
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##### 1. Clone
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```shell
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git clone https://github.com/debanjum/khoj & & cd khoj
```
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##### 2. Configure
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- **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 )
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##### 3. Run
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```shell
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docker-compose up -d
```
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*Note: The first run will take time. Let it run, it\'s mostly not hung, just generating embeddings*
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##### 4. Upgrade
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```shell
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docker-compose build --pull
```
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#### Using Conda
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##### 1. Install Dependencies
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- [Install Conda ](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html )
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##### 2. Install Khoj
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```shell
git clone https://github.com/debanjum/khoj & & cd khoj
conda env create -f config/environment.yml
conda activate khoj
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python3 -m pip install pyqt6 # As conda does not support pyqt6 yet
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```
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##### 3. Configure
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- 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
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##### 4. Run
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```shell
python3 -m src.main -vv
```
Load ML model, generate embeddings and expose API to query notes, images, transactions etc specified in config YAML
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##### 5. Upgrade
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```shell
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cd khoj
git pull origin master
conda deactivate khoj
conda env update -f config/environment.yml
conda activate khoj
```
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### Test
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```shell
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pytest
```
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## Credits
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- [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