Convert Readme to Markdown from Org as better support on Github

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Debanjum Singh Solanky 2022-07-29 17:06:34 +04:00
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[[https://github.com/debanjum/khoj/actions/workflows/test.yml/badge.svg]] [[https://github.com/debanjum/khoj/actions/workflows/build.yml/badge.svg]]
* Khoj
/A natural language search engine for your personal notes, transactions and images/
** Table of Contents
- [[https://github.com/debanjum/khoj#Features][Features]]
- [[https://github.com/debanjum/khoj#Demo][Demo]]
- [[https://github.com/debanjum/khoj#Description][Description]]
- [[https://github.com/debanjum/khoj#Analysis][Analysis]]
- [[https://github.com/debanjum/khoj#Architecture][Architecture]]
- [[https://github.com/debanjum/khoj#Setup][Setup]]
- [[https://github.com/debanjum/khoj#Clone][Clone]]
- [[https://github.com/debanjum/khoj#Configure][Configure]]
- [[https://github.com/debanjum/khoj#Run][Run]]
- [[https://github.com/debanjum/khoj#Use][Use]]
- [[https://github.com/debanjum/khoj#Upgrade][Upgrade]]
- [[https://github.com/debanjum/khoj#Troubleshooting][Troubleshooting]]
- [[https://github.com/debanjum/khoj#Miscellaneous][Miscellaneous]]
- [[https://github.com/debanjum/khoj#Development-setup][Development Setup]]
- [[https://github.com/debanjum/khoj#Setup-on-local-machine][Setup on Local Machine]]
- [[https://github.com/debanjum/khoj#Upgrade-on-local-machine][Upgrade on Local Machine]]
- [[https://github.com/debanjum/khoj#Run-unit-tests][Run Unit Tests]]
- [[https://github.com/debanjum/khoj#Performance][Performance]]
- [[https://github.com/debanjum/khoj#Query-performance][Query Performance]]
- [[https://github.com/debanjum/khoj#Indexing-performance][Indexing Performance]]
- [[https://github.com/debanjum/khoj#Miscellaneous-1][Miscellaneous]]
- [[https://github.com/debanjum/khoj#Acknowledgments][Acknowledgments]]
** 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 relatively 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 [[./src/interface/web/index.html][Web Browser]], [[./src/interface/emacs/khoj.el][Emacs]] or the [[http://localhost:8000/docs][API]]
** 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 [[https://github.com/debanjum/khoj/tree/master/src/interface/emacs][khoj.el readme]]
- Top result is what we are looking for, the [[https://github.com/debanjum/khoj/tree/master/src/interface/emacs#installation][section to Install Khoj.el on Emacs]]
*** 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
#+begin_src shell
git clone https://github.com/debanjum/khoj && cd khoj
#+end_src
*** 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 [[./config/sample_config.yml][sample_config.yml]]
*** 3. Run
#+begin_src shell
docker-compose up -d
#+end_src
/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 [[./src/interface/web/index.html][index.html]] in your browser
- *Khoj via Emacs*
- [[https://github.com/debanjum/khoj/tree/master/src/interface/emacs#installation][Install]] [[./src/interface/emacs/khoj.el][khoj.el]]
- Run ~M-x khoj <user-query>~
- *Khoj via API*
- See [[http://localhost:8000/docs][Khoj FastAPI Docs]]
- [[http://localhost:8000/search?q=%22what%20is%20the%20meaning%20of%20life%22][Query]]
- [[http://localhost:8000/regenerate?t=ledger][Regenerate Embeddings]]
- [[https://localhost:8000/ui][Configure Application]]
** Upgrade
#+begin_src shell
docker-compose build --pull
#+end_src
** Troubleshooting
- Symptom: Errors out with "Killed" in error message
- Fix: Increase RAM available to Docker Containers in Docker Settings
- Refer: [[https://stackoverflow.com/a/50770267][StackOverflow Solution]], [[https://docs.docker.com/desktop/mac/#resources][Configure Resources on Docker for Mac]]
- Symptom: Errors out complaining about Tensors mismatch, null etc
- Mitigation: Delete content-type > image section from docker_sample_config.yml
** Miscellaneous
- The experimental [[localhost:8000/chat][chat]] API endpoint uses the [[https://openai.com/api/][OpenAI 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. [[https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html][Install Conda]] [Required]
3. Install Exiftool [Optional]
#+begin_src shell
sudo apt-get -y install libimage-exiftool-perl
#+end_src
**** 2. Install Khoj
#+begin_src shell
git clone https://github.com/debanjum/khoj && cd khoj
conda env create -f config/environment.yml
conda activate khoj
#+end_src
**** 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
#+begin_src shell
python3 -m src.main -c=config/sample_config.yml -vv
#+end_src
*** Upgrade On Local Machine
#+begin_src shell
cd khoj
git pull origin master
conda deactivate khoj
conda env update -f config/environment.yml
conda activate khoj
#+end_src
*** Run Unit Tests
#+begin_src shell
pytest
#+end_src
** 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
** Acknowledgments
- [[https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1][Multi-QA MiniLM Model]], [[https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2][All MiniLM Model]] for Text Search. See [[https://www.sbert.net/examples/applications/retrieve_rerank/README.html][SBert Documentation]]
- [[https://github.com/openai/CLIP][OpenAI CLIP Model]] for Image Search. See [[https://www.sbert.net/examples/applications/image-search/README.html][SBert Documentation]]
- Charles Cave for [[http://members.optusnet.com.au/~charles57/GTD/orgnode.html][OrgNode Parser]]
- [[https://mooz.github.io/org-js/][Org.js]] to render Org-mode results on the Web interface
- [[https://github.com/markdown-it/markdown-it][Markdown-it]] to render Markdown results on the Web interface
- Sven Marnach for [[https://github.com/smarnach/pyexiftool/blob/master/exiftool.py][PyExifTool]]

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![](https://github.com/debanjum/khoj/actions/workflows/test.yml/badge.svg)
![](https://github.com/debanjum/khoj/actions/workflows/build.yml/badge.svg)
# Khoj
*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)
- [Troubleshooting](#Troubleshooting)
- [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)
- [Acknowledgments](#Acknowledgments)
## 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 relatively 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
```
## Troubleshooting
- 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
## Acknowledgments
- [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)