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Debanjum Singh Solanky d27dc71dfe Use encoding of each file set in indexer request to read file 
Get encoding type from multi-part/form-request body for each file
Read text files as utf-8 and pdfs, images as binary
2023-10-17 04:58:12 -07:00
.github/workflows
Improve docker builds for local hosting (#476)
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config
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docs
Update setup instructions
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scripts
Upgrade bump_version script to handle release and post-release commit
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src
Use encoding of each file set in indexer request to read file
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tests
Update tests to test multi-part/form method of pushing files to index
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.dockerignore
Use pypi khoj to fix docker builds and dockerize github workflow
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.gitignore
Add front-end Electron application for Khoj local file syncing (#473)
2023-09-06 12:04:18 -07:00
.pre-commit-config.yaml
Run mypy checks in test workflow and on push (via pre-commit)
2023-02-17 16:08:56 -06:00
docker-compose.yml
Improve docker builds for local hosting (#476)
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Dockerfile
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2023-09-18 15:38:18 -07:00
LICENSE
Add, configure and run pre-commit locally and in test workflow
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manifest.json
Release Khoj version 0.12.3
2023-09-26 22:41:11 -07:00
pyproject.toml
Use multi-part form to receive files to index on server
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README.md
Use 500px png of khoj logo instead svg for much smaller asset size
2023-08-07 18:27:11 -07:00
versions.json
Release Khoj version 0.12.3
2023-09-26 22:41:11 -07:00

README.md

Khoj Logo

test dockerize pypi

An AI personal assistant for your digital brain

Khoj is a desktop application to search and chat with your notes, documents and images.
It is an offline-first, open source AI personal assistant accessible from your Emacs, Obsidian or Web browser.
It works with jpeg, markdown, notion, org-mode, pdf files and github repositories.

🔎 Search 💬 Chat
Quickly retrieve relevant documents using natural language Get answers and create content from your existing knowledge base
Does not need internet Can be configured to work without internet
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Description
No description provided
Readme AGPL-3.0 116 MiB
Languages
Python 51%
TypeScript 36.1%
CSS 4.1%
HTML 3.2%
Emacs Lisp 2.4%
Other 3.1%