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bf1ae038cb
- Pillow already supports reading XMP metadata from Images
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252 lines
8.7 KiB
Markdown
252 lines
8.7 KiB
Markdown
# Khoj 🦅
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[](https://github.com/debanjum/khoj/actions/workflows/build.yml)
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[](https://github.com/debanjum/khoj/actions/workflows/test.yml)
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[](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*
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## Table of Contents
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- [Features](#Features)
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- [Demo](#Demo)
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- [Description](#Description)
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- [Analysis](#Analysis)
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- [Interfaces](#Interfaces)
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- [Architecture](#Architecture)
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- [Setup](#Setup)
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- [Install](#1-Install)
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- [Configure](#2-Configure)
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- [Run](#3-Run)
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- [Use](#Use)
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- [Upgrade](#Upgrade)
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- [Troubleshoot](#Troubleshoot)
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- [Miscellaneous](#Miscellaneous)
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- [Performance](#Performance)
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- [Query Performance](#Query-performance)
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- [Indexing Performance](#Indexing-performance)
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- [Miscellaneous](#Miscellaneous-1)
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- [Development](#Development)
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- [Setup](#Setup)
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- [Using Pip](#Using-Pip)
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- [Using Docker](#Using-Docker)
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- [Using Conda](#Test)
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- [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)
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- **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
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- **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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## Demo
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https://user-images.githubusercontent.com/6413477/184735169-92c78bf1-d827-4663-9087-a1ea194b8f4b.mp4
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### Description
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- Install Khoj via pip
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- Start Khoj app
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- Add this readme and [khoj.el readme](https://github.com/debanjum/khoj/tree/master/src/interface/emacs) as org-mode for Khoj to index
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- 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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### Analysis
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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?*
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- 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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### Interfaces
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## Architecture
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## Setup
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### 1. Install
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```shell
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pip install khoj-assistant
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```
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### 2. Start App
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```shell
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khoj
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```
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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 load ML model, generates embeddings and expose the search API
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## Use
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- **Khoj via Web**
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- Open <http://localhost:8000/> via desktop interface or directly
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- **Khoj via Emacs**
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- [Install](https://github.com/debanjum/khoj/tree/master/src/interface/emacs#installation) [khoj.el](./src/interface/emacs/khoj.el)
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- Run `M-x khoj <user-query>`
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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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## Upgrade
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```shell
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pip install --upgrade khoj-assistant
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```
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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
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- 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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## Miscellaneous
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- The beta [chat](http://localhost:8000/beta/chat) and [search](http://localhost:8000/beta/search) API endpoints use [OpenAI API](https://openai.com/api/)
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- It is disabled by default
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- To use it add your `openai-api-key` via the app configure screen
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- 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
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### 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
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- 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
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- Testing done on a Mac M1 and a \>100K line corpus of notes
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- Search, indexing on a GPU has not been tested yet
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## Development
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### Setup
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#### Using Pip
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##### 1. Install
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```shell
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git clone https://github.com/debanjum/khoj && cd khoj
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python3 -m venv .venv && source .venv/bin/activate
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pip install -e .
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```
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##### 2. Configure
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- Copy the `config/khoj_sample.yml` to `~/.khoj/khoj.yml`
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- Set `input-files` or `input-filter` in each relevant `content-type` section of `~/.khoj/khoj.yml`
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- Set `input-directories` field in `image` `content-type` section
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- Delete `content-type` and `processor` sub-section(s) irrelevant for your use-case
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##### 3. Run
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```shell
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khoj -vv
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```
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Load ML model, generate embeddings and expose API to query notes, images, transactions etc specified in config YAML
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##### 4. Upgrade
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```shell
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# 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
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# 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
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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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```
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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
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- **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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```
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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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```
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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
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git clone https://github.com/debanjum/khoj && cd khoj
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conda env create -f config/environment.yml
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conda activate khoj
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```
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##### 3. Configure
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- Copy the `config/khoj_sample.yml` to `~/.khoj/khoj.yml`
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- Set `input-files` or `input-filter` in each relevant `content-type` section of `~/.khoj/khoj.yml`
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- Set `input-directories` field in `image` `content-type` section
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- Delete `content-type`, `processor` sub-sections irrelevant for your use-case
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##### 4. Run
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```shell
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python3 -m src.main -vv
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```
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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
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git pull origin master
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conda deactivate khoj
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conda env update -f config/environment.yml
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conda activate khoj
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```
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### Test
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```shell
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pytest
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```
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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)
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- [OpenAI CLIP Model](https://github.com/openai/CLIP) for Image Search. See [SBert Documentation](https://www.sbert.net/examples/applications/image-search/README.html)
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- Charles Cave for [OrgNode Parser](http://members.optusnet.com.au/~charles57/GTD/orgnode.html)
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- [Org.js](https://mooz.github.io/org-js/) to render Org-mode results on the Web interface
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- [Markdown-it](https://github.com/markdown-it/markdown-it) to render Markdown results on the Web interface
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