[](https://github.com/khoj-ai/khoj/actions/workflows/test.yml) [](https://github.com/khoj-ai/khoj/pkgs/container/khoj) [](https://pypi.org/project/khoj-assistant/) # Khoj *An AI personal assistant for your digital brain* Welcome to the Khoj Docs! This is the best place to get started with Khoj. Check out our [Github](https://github.com/khoj-ai/khoj) to explore the code or our [Website](https://khoj.dev) for an invite up to Khoj cloud. Khoj gives you lightning fast, offline search on your personal machine and gives you the power to talk to your notes. **Supported Plugins** [](https://github.com/khoj-ai/khoj/tree/master/src/interface/obsidian#readme) [](https://github.com/khoj-ai/khoj/tree/master/src/interface/emacs#readme) ## Features - **Search** - **Local**: Your personal data stays local. All search and indexing is done on your machine. *Unlike chat which requires access to GPT.* - **Incremental**: Incremental search for a fast, search-as-you-type experience - **Chat** - **Faster answers**: Find answers faster, smoother than search. No need to manually scan through your notes to find answers. - **Iterative discovery**: Iteratively explore and (re-)discover your notes - **Assisted creativity**: Smoothly weave across answers retrieval and content generation - **General** - **Natural**: Advanced natural language understanding using Transformer based ML Models - **Pluggable**: Modular architecture makes it easy to plug in new data sources, frontends and ML models - **Multiple Sources**: Index your Org-mode and Markdown notes, PDF files, Github repositories, and Photos - **Multiple Interfaces**: Interact from your [Web Browser](https://docs.khoj.dev/#/web), [Emacs](https://docs.khoj.dev/#/emacs) or [Obsidian](https://docs.khoj.dev/#/obsidian) ## Install [Click here](/setup) for full setup instructions. ## Supported data sources - markdown* - org-mode* - pdf* - images* - github - notion \* These data sources are offline only. If you're using Github or Notion, you can get on a waitlist for [Khoj Cloud](https://khoj.dev). ## 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