# Khoj 🦅
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*A natural language search engine for your personal notes, transactions and images*

## Table of Contents

- [Features](#Features)
- [Demo](#Demo)
  - [Description](#Description)
  - [Analysis](#Analysis)
- [Architecture](#Architecture)
- [Setup](#Setup)
  - [Clone](#Clone)
  - [Configure](#Configure)
  - [Run](#Run)
- [Use](#Use)
- [Upgrade](#Upgrade)
- [Troubleshoot](#Troubleshoot)
- [Miscellaneous](#Miscellaneous)
- [Development Setup](#Development-setup)
  - [Setup on Local Machine](#Setup-on-local-machine)
  - [Upgrade on Local Machine](#Upgrade-on-local-machine)
  - [Run Unit Tests](#Run-unit-tests)
- [Performance](#Performance)
  - [Query Performance](#Query-performance)
  - [Indexing Performance](#Indexing-performance)
  - [Miscellaneous](#Miscellaneous-1)
- [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#miscellaneous)
- **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 using a [Web Browser](./src/interface/web/index.html), [Emacs](./src/interface/emacs/khoj.el) or the [API](http://localhost:8000/docs)

## Demo

<https://user-images.githubusercontent.com/6413477/181664862-31565b0a-0e64-47e1-a79a-599dfc486c74.mp4>

### Description

- User searches for \"*Setup editor*\"
- The demo looks for the most relevant section in this readme and the [khoj.el readme](https://github.com/debanjum/khoj/tree/master/src/interface/emacs)
- 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)

### 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 is idle

## Architecture

![](https://github.com/debanjum/khoj/blob/master/docs/khoj_architecture.png)

## Setup

### 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 [sample_config.yml](./config/sample_config.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*

## Use

- **Khoj via Web**
  - Go to <http://localhost:8000/> or open [index.html](./src/interface/web/index.html) in your browser
- **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>`
- **Khoj via API**
  - See [Khoj FastAPI Docs](http://localhost:8000/docs)
  - [Query](http://localhost:8000/search?q=%22what%20is%20the%20meaning%20of%20life%22)
  - [Regenerate Embeddings](http://localhost:8000/regenerate?t=ledger)
  - [Configure Application](https://localhost:8000/ui)

## Upgrade

``` shell
docker-compose build --pull
```

## Troubleshoot

- Symptom: 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)
- Symptom: Errors out complaining about Tensors mismatch, null etc
  - Mitigation: Delete content-type > image section from `docker_sample_config.yml`

## Miscellaneous

- The experimental [chat](localhost:8000/chat) API endpoint uses the [OpenAI API](https://openai.com/api/)
    - It is disabled by default
    - To use it add your `openai-api-key` to config.yml

## Development Setup

### Setup on Local Machine

1. Install Dependencies
   1. Install Python3 \[Required\]
   2. [Install Conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html) \[Required\]
   3. Install Exiftool \[Optional\]
      ``` shell
      sudo apt-get -y install libimage-exiftool-perl
      ```

2. Install Khoj
   ``` shell
   git clone https://github.com/debanjum/khoj && cd khoj
   conda env create -f config/environment.yml
   conda activate khoj
   ```

3. Configure
   - Configure files/directories to search in `content-type` section of `sample_config.yml`
   - To run application on test data, update file paths containing `/data/` to `tests/data/` in `sample_config.yml`
     - Example replace `/data/notes/*.org` with `tests/data/notes/*.org`

4. Run
   Load ML model, generate embeddings and expose API to query notes, images, transactions etc specified in config YAML

   ``` shell
   python3 -m src.main -c=config/sample_config.yml -vv
   ```

### Upgrade On Local Machine

``` shell
cd khoj
git pull origin master
conda deactivate khoj
conda env update -f config/environment.yml
conda activate khoj
```

### Run Unit Tests

``` shell
pytest
```

## Performance

### Query performance

- Semantic search using the bi-encoder is fairly fast at \<5 ms
- Reranking using the cross-encoder is slower at \<2s on 15 results. Tweak `top_k` to tradeoff speed for accuracy of results
- Applying explicit filters is very slow currently at \~6s. This is because the filters are rudimentary. Considerable speed-ups can be achieved using indexes etc

### Indexing performance

- Indexing is more strongly impacted by the size of the source data
- Indexing 100K+ line corpus of notes takes 6 minutes
- Indexing 4000+ images takes about 15 minutes and more than 8Gb of RAM
- Once <https://github.com/debanjum/khoj/issues/36> is implemented, it should only take this long on first run

### Miscellaneous

- Testing done on a Mac M1 and a \>100K line corpus of notes
- Search, indexing on a GPU has not been tested yet

## 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
- Sven Marnach for [PyExifTool](https://github.com/smarnach/pyexiftool/blob/master/exiftool.py)