• Semantic Search
  • Dependencies
  • Install
  • Configure
  • Run
  • Use
  • Upgrade
  • Acknowledgments

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

• Python3
• Miniconda

Install

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

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

• 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

Upgrade

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

Acknowledgments

• MiniLM Model for Asymmetric Text Search. See SBert Documentation
• OpenAI CLIP Model for Image Search. See SBert Documentation
• Charles Cave for OrgNode Parser
• Sven Marnach for PyExifTool