sij/khoj: Mirror of khoj from Github

sij/khoj

mirror of https://github.com/khoj-ai/khoj.git synced 2024-11-23 15:38:55 +01:00

Mirror of khoj from Github

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Saba 4ae8c15170 Clean the Dockerfile - Use /app as the working directory - Clarify comment to explain why the ENTRYPOINT is constructed as it is - Move explanations for the argument to docker-compose, where it's set - Copy required artifacts from the first build image into the subsequent one (exiftool)		2022-01-24 14:08:55 -05:00
.github/workflows	Try cache conda build step using online docs	2021-12-15 11:48:14 +05:30
src	Rename RawConfig Types for Consistency	2022-01-14 20:54:38 -05:00
tests	Rename RawConfig Types for Consistency	2022-01-14 20:54:38 -05:00
views	Fix input text behavior for null/empty value fields	2021-12-04 10:45:48 -05:00
.gitignore	Set up basic ui page with no functionality	2021-11-26 14:51:11 -05:00
docker-compose.yml	Rename web to server in docker-compose.yml	2022-01-24 00:14:01 -05:00
docker_sample_config.yml	Working example with docker-compose	2022-01-23 23:44:38 -05:00
Dockerfile	Clean the Dockerfile	2022-01-24 14:08:55 -05:00
environment.yml	Merge branch 'master' of github.com:debanjum/semantic-search into add-summarize-capability-to-chat-bot	2021-12-20 13:30:42 +05:30
LICENSE	Add Readme, License. Update .gitignore	2021-08-15 22:52:37 -07:00
README.org	Fix url error in README	2022-01-13 16:28:46 -08:00
sample_config.yml	Save Image Search Model to Disk	2022-01-14 17:36:59 -05:00

Semantic Search

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

All data is processed locally. User can interface with semantic-search app via Emacs, API or Commandline

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

sudo apt-get -y install libimage-exiftool-perl

Configure application search types and their underlying data source/files in sample_config.yml Use the sample_config.yml as reference

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

python3 -m src.main -c=sample_config.yml -vv

Semantic Search via Emacs
- Install semantic-search.el
- Run M-x semantic-search <user-query>
Semantic Search via API
- Query: GET http://localhost:8000/search?q="What is the meaning of life"&t=notes
- Regenerate Embeddings: GET http://localhost:8000/regenerate?t=image
- Semantic Search API Docs

  cd semantic-search
  git pull origin master
  conda env update -f environment.yml
  conda activate semantic-search