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Add Table of Contents, Features, Performance Details to Readme
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README.org
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README.org
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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]]
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* Khoj
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/Natural language search engine for your personal notes, transactions and images/
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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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- [[https://github.com/debanjum/khoj#Features][Features]]
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- [[https://github.com/debanjum/khoj#Demo][Demo]]
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- [[https://github.com/debanjum/khoj#Description][Description]]
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- [[https://github.com/debanjum/khoj#Analysis][Analysis]]
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- [[https://github.com/debanjum/khoj#Architecture][Architecture]]
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- [[https://github.com/debanjum/khoj#Setup][Setup]]
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- [[https://github.com/debanjum/khoj#Clone][Clone]]
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- [[https://github.com/debanjum/khoj#Configure][Configure]]
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- [[https://github.com/debanjum/khoj#Run][Run]]
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- [[https://github.com/debanjum/khoj#Use][Use]]
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- [[https://github.com/debanjum/khoj#Upgrade][Upgrade]]
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- [[https://github.com/debanjum/khoj#Troubleshooting][Troubleshooting]]
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- [[https://github.com/debanjum/khoj#Miscellaneous][Miscellaneous]]
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- [[https://github.com/debanjum/khoj#Development-setup][Development Setup]]
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- [[https://github.com/debanjum/khoj#Setup-on-local-machine][Setup on Local Machine]]
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- [[https://github.com/debanjum/khoj#Upgrade-on-local-machine][Upgrade on Local Machine]]
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- [[https://github.com/debanjum/khoj#Run-unit-tests][Run Unit Tests]]
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- [[https://github.com/debanjum/khoj#Performance][Performance]]
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- [[https://github.com/debanjum/khoj#Query-performance][Query Performance]]
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- [[https://github.com/debanjum/khoj#Indexing-performance][Indexing Performance]]
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- [[https://github.com/debanjum/khoj#Miscellaneous-1][Miscellaneous]]
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- [[https://github.com/debanjum/khoj#Acknowledgments][Acknowledgments]]
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** Features
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- Advanced Natural language understanding using Transformer based ML Models
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- Your personal data stays local. All search, indexing is done on your machine[[https://github.com/debanjum/khoj#miscellaneous][*]]
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- Index Org-mode and Markdown notes, Beancount transactions and Photos
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- Interact with Khoj using a [[./src/interface/web/index.html][Web Browser]], [[./src/interface/emacs/khoj.el][Emacs]] or the [[http://localhost:8000/docs][API]].
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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 relatively 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 [[./src/interface/web/index.html][Web Browser]], [[./src/interface/emacs/khoj.el][Emacs]] or the [[http://localhost:8000/docs][API]]
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** Demo
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https://user-images.githubusercontent.com/6413477/181664862-31565b0a-0e64-47e1-a79a-599dfc486c74.mp4
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@@ -18,8 +44,8 @@
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- 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]]
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*** Analysis
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- The top result does not have any words from the query
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- Does the model understand that Emacs is an editor?
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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 is idle
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@@ -115,14 +141,31 @@
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conda activate khoj
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#+end_src
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*** Run Unit tests
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*** Run Unit Tests
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#+begin_src shell
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pytest
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#+end_src
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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 <5 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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- 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.
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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 6 minutes
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- Indexing 4000+ images takes about 15 minutes and more than 8Gb of RAM
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- Once https://github.com/debanjum/khoj/issues/36 is implemented, it should only take this long on first run
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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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** Acknowledgments
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- [[https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1][Multi-QA MiniLM Model]] for Asymmetric Text Search. See [[https://www.sbert.net/examples/applications/retrieve_rerank/README.html][SBert Documentation]]
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- [[https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2][All MiniLM Model]] for Symmetric Text Search
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- [[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]]
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- [[https://github.com/openai/CLIP][OpenAI CLIP Model]] for Image Search. See [[https://www.sbert.net/examples/applications/image-search/README.html][SBert Documentation]]
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- Charles Cave for [[http://members.optusnet.com.au/~charles57/GTD/orgnode.html][OrgNode Parser]]
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- Sven Marnach for [[https://github.com/smarnach/pyexiftool/blob/master/exiftool.py][PyExifTool]]
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- [[https://mooz.github.io/org-js/][Org.js]] to render Org-mode results on the Web interface
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- [[https://github.com/markdown-it/markdown-it][Markdown-it]] to render Markdown results on the Web interface
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- Sven Marnach for [[https://github.com/smarnach/pyexiftool/blob/master/exiftool.py][PyExifTool]]
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- In Emacs: Call ~khoj~ using keybinding ~C-c s~ or ~M-x khoj~
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- On Web: Open http://localhost:8000/
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2. Query in Natural Language
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2. Query Incrementally in Natural Language
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e.g "What is the meaning of life?" "What are my life goals?"
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*Note: It takes about 4s on a Mac M1 and a >100K line corpus of notes*
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3. (Optional) Narrow down results further
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3. Apply filters to narrow down results further
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Include/Exclude specific words or date range from results by updating query with below query format
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