khoj/tests/data/markdown/main_readme.md

Khoj

Allow natural language search on user content like notes, images, transactions using transformer ML models

User can interface with Khoj via Web, Emacs or the API. All search is done locally*

Demo

https://user-images.githubusercontent.com/6413477/168417719-8a8bc4e5-8404-42b2-89a7-4493e3d2582c.mp4

Setup

1. Clone

git clone https://github.com/debanjum/khoj && cd khoj

2. Configure

• [Required] Update docker-compose.yml to mount your images, (org-mode or markdown) notes and beancount directories
• [Optional] Edit application configuration in khoj_sample.yml

3. Run

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 API
  • See Khoj API Docs
  • Query
  • Update Index
  • Configure Application
• Khoj via Emacs
  • Install khoj.el
  • Run M-x khoj <user-query>

Run Unit tests

pytest

Upgrade

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, Configure Resources on Docker for Mac
• Symptom: Errors out complaining about Tensors mismatch, null etc
  • Mitigation: Delete content-type > image section from dockersampleconfig.yml

Miscellaneous

• The experimental chat API endpoint uses the 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. 1. Install Dependencies

   1. Install Python3 [Required]

   2. Install Conda

      Required

2. 2. Install Khoj

   git clone https://github.com/debanjum/khoj && cd khoj
   conda env create -f config/environment.yml
   conda activate khoj
   

3. 3. Configure

   • Configure files/directories to search in content-type section of khoj_sample.yml
   • To run application on test data, update file paths containing /data/ to tests/data/ in khoj_sample.yml
     • Example replace /data/org/*.org with tests/data/org/*.org

4. 4. Run

   Load ML model, generate embeddings and expose API to query notes, images, transactions etc specified in config YAML

   python3 -m src.khoj.main -c=config/khoj_sample.yml -vv
   

Upgrade On Local Machine

cd khoj
git pull origin master
conda deactivate khoj
conda env update -f config/environment.yml
conda activate khoj

Acknowledgments

• Multi-QA MiniLM Model for Asymmetric Text Search. See SBert Documentation
• OpenAI CLIP Model for Image Search. See SBert Documentation
• Charles Cave for OrgNode Parser