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Saba 77fa8718d9 Working example with docker-compose 
Still need quite a bit of clean-up, but this adds a working docker-compose + Dockerfile setup
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README.org

https://github.com/debanjum/semantic-search/actions/workflows/build.yml/badge.svg

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

Dependencies

Install 

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

Install Environmental Dependencies 

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

Configure

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

Run

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

Use

Upgrade 

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

Acknowledgments